We undertake a comprehensive investigation into the distribution of in situ stars within Milky Way-like galaxies, leveraging TNG50 simulations and comparing their predictions with data from the H3 survey. Our analysis reveals that 28% of galaxies demonstrate reasonable agreement with H3, while only 12% exhibit excellent alignment in their profiles, regardless of the specific spatial cut employed to define in situ stars. To uncover the underlying factors contributing to deviations between TNG50 and H3 distributions, we scrutinise correlation coefficients among internal drivers (e.g. virial radius, star formation rate [SFR]) and merger-related parameters (such as the effective mass-ratio, mean distance, average redshift, total number of mergers, average spin-ratio, and maximum spin alignment between merging galaxies). Notably, we identify significant correlations between deviations from observational data and key parameters such as the median slope of virial radius, mean SFR values, and the rate of SFR change across different redshift scans. Furthermore, positive correlations emerge between deviations from observational data and parameters related to galaxy mergers. We validate these correlations using the Random Forest Regression method. Our findings underscore the invaluable insights provided by the H3 survey in unravelling the cosmic history of galaxies akin to the Milky Way, thereby advancing our understanding of galactic evolution and shedding light on the formation and evolution of Milky Way-like galaxies in cosmological simulations.

The World Cancer Research Fund and the American Institute for Cancer Research recommend a plant-based diet to cancer survivors, which may reduce chronic inflammation and excess adiposity associated with worse survival. We investigated associations of plant-based dietary patterns with inflammation biomarkers and body composition in the Pathways Study, in which 3659 women with breast cancer provided validated food frequency questionnaires approximately 2 months after diagnosis. We derived three plant-based diet indices: overall plant-based diet index (PDI), healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI). We assayed circulating inflammation biomarkers related to systemic inflammation (high-sensitivity C-reactive protein [hsCRP]), pro-inflammatory cytokines (IL-1β, IL-6, IL-8, TNF-α) and anti-inflammatory cytokines (IL-4, IL-10, IL-13). We estimated areas (cm2) of muscle and visceral and subcutaneous adipose tissue (VAT and SAT) from computed tomography scans. Using multivariable linear regression, we calculated the differences in inflammation biomarkers and body composition for each index. Per 10-point increase for each index: hsCRP was significantly lower by 6·9 % (95 % CI 1·6%, 11·8%) for PDI and 9·0 % (95 % CI 4·9%, 12·8%) for hPDI but significantly higher by 5·4 % (95 % CI 0·5%, 10·5%) for uPDI, and VAT was significantly lower by 7·8 cm2 (95 % CI 2·0 cm2, 13·6 cm2) for PDI and 8·6 cm2 (95 % CI 4·1 cm2, 13·2 cm2) for hPDI but significantly higher by 6·2 cm2 (95 % CI 1·3 cm2, 11·1 cm2) for uPDI. No significant associations were observed for other inflammation biomarkers, muscle, or SAT. A plant-based diet, especially a healthful plant-based diet, may be associated with reduced inflammation and visceral adiposity among breast cancer survivors.

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modelled as wave–wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave–wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error-mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

OBJECTIVES/GOALS: We aimed to conduct an updated genome-wide meta-analysis of keloids in expanded populations, including those most afflicted by keloids. Our overall objective was to improve understanding of keloid development though the identification and further characterization of keloid-associated genes with genetically predicted gene expression (GPGE). METHODS/STUDY POPULATION: We used publicly available summary statistics from several large-scale DNA biobanks, including the UK Biobank, FinnGen, and Biobank Japan. We also leveraged data from the Million Veterans Program and performed genome-wide association studies of keloids in BioVU and eMERGE. For each of these datasets, cases were determined from ICD-9/ICD-10 codes and phecodes. With these data we conducted fixed effects meta-analysis, both across ancestries and stratified by broad ancestry groups. This approach allowed us to consider cumulative evidence for genetic risk factors for keloids and explore potential ancestry-specific components of risk. We used FUMA for functional annotation of results and LDSC to estimate ancestry-specific heritability. We performed GPGE analysis using S-PrediXcan with GTEx v8 tissues. RESULTS/ANTICIPATED RESULTS: We detected 30 (23 novel) genomic risk loci in the cross-ancestry analysis. Major risk loci were broadly consistent between ancestries, with variable effects. Keloid heritability estimates from LDSC were 6%, 21%, and 34% for European, East Asian, and African ancestry, respectively. The top hit (P = 1.7e-77) in the cross-ancestry analysis was at a replicated variant (rs10863683) located downstream of LINC01705. GPGE analysis identified an association between decreased risk of keloids and increased expression of LINC01705 in fibroblasts (P = 3.6e10-20), which are important in wound healing. The top hit in the African-ancestry analysis (P = 5.5e-31) was a novel variant (rs34647667) in a conserved region downstream of ITGA11. ITGA11 encodes a collagen receptor and was previously associated with uterine fibroids. DISCUSSION/SIGNIFICANCE: This work significantly increases the yield of discoveries from keloid genetic association studies, describing both common and ancestry-specific effects. Stark differences in heritability support a potential adaptive origin for keloid disparities. Further work will continue to examine keloids in the broader context of other fibrotic diseases.

Due to the safety threats caused by icing, the de-icing system is essential in the aviation industry. As an effective method, the electromechanical de-icing system (EDS) is a new ice-protection system based on mechanical vibration principles. For the majority of the current research on system de-icing capability estimation, the effect of impedance-matching is not considered. Impedance matching plays a very important role in improving the performance of the electromechanical system, so we must also consider the impact of impedance matching when designing the EDS. In the present study, a de-icing capability prediction method considering the impact of an impedance-matching device is established based on experimental and numerical methods. The results indicate that the impedance-matching effect has no impact on the mechanical vibration of the structure for the same load power. Meanwhile, impedance-matching devices can significantly improve the power factor and increase the interface shear stress/strain for de-icing. Eight different vibrational modes were tested, and the experimental results showed that the actual interface shear strain after impedance matching is inversely proportional to the de-icing time. The verification experiments were conducted and the accuracy of the proposed prediction method was verified.

NEWMOD®, developed by R.C. Reynolds, Jr., has been an important tool for evaluating quantitatively X-ray diffraction (XRD) patterns from interstratified clay minerals for more than 20 years. However, a significant drawback to the NEWMOD® approach is that analyses are done by forward simulation, making results sensitive to user input and starting-model assumptions. In the present study, a reverse-fitting procedure was implemented in a new program, FITMOD, which automatically minimizes the differences between experimental and simulated XRD patterns. The differences are minimized by varying model parameters (such as Reichweite, crystal-size distribution, cation content, type of disorder, etc.) using the downhill simplex method. The downhill simplex method is a non-linear optimization technique for determining minima of functions. This method does not require calculation of the derivatives of the functions being minimized, an important consideration with many of the parameters in NEWMOD- type simulations. Instead, the downhill simplex method calculates pseudo-derivatives by evaluating sufficient points to define a derivative for each independent variable. The performance of FITMOD was evaluated by fitting a series of synthetic XRD patterns generated by NEWMOD+, yielding agreement factors, Rwp, of <0.3%. As long as the correct interstratified system was specified (e.g. illite-smectite), excellent fits were obtained irrespective of the starting parameters for the simulations. FITMOD was also tested using experimental XRD patterns, which gave very good fits, in agreement with previously published results. The optimization routine yields good fits for both synthetic and experimental XRD profiles in a reasonable time, with the possibility of varying all important structural parameters. FITMOD automatically provides optimum fits to experimental XRD data without operator bias, and fitting efficiency and accuracy were, therefore, significantly improved.

A series of organoclays with monolayers, bilayers, pseudotrilayers, paraffin monolayers and paraffin bilayers were prepared from montmorillonite by ion exchange with hexadecyltrimethylammonium bromide (HDTMAB). The HDTMAB concentrations used for preparing the organoclays were 0.5, 0.7, 1.0, 1.5, 2.0 and 2.5 times the montmorillonite cation exchange capacity (CEC). The microstructural parameters, including the BET-N2 surface area, pore volume, pore size, and surfactant loading and distribution, were determined by X-ray diffraction, N2 adsorption-desorption and high-resolution thermogravimetric analysis (HRTG). The BET-N2 surface area decreased from 55 to 1 m2/g and the pore volume decreased from 0.11 to 0.01 cm3/g as surfactant loading was increased from Na-Mt to 2.5CEC-Mt. The average pore diameter increased from 6.8 to 16.3 nm as surfactant loading was increased. After modifying montmorillonite with HDTMAB, two basic organoclay models were proposed on the basis of HRTG results: (1) the surfactant mainly occupied the clay interlayer space (0.5CEC-Mt, 0.7CEC-Mt, 1.0CEC-Mt); and (2) both the clay interlayer space and external surface (1.5CEC-Mt, 2.0CEC-Mt, 2.5CEC-Mt) were modified by surfactant. In model 1, the sorption mechanism of p-nitrophenol to the organoclay at a relatively low concentration involved both surface adsorption and partitioning, whereas, in model 2 it mainly involved only partitioning. This study demonstrates that the distribution of adsorbed surfactant and the arrangement of adsorbed HDTMA+ within the clay interlayer space control the efficiency and mechanism of sorption by the organoclay rather than BET-N2 surface area, pore volume, and pore diameter.

The thermal stability of surfactant-modified clays plays a key role in the synthesis and processing of organoclay-based nanocomposites. Differential thermal analysis (DTA), thermogravimetric measurement and differential scanning calorimetry (DSC) were used in this study to characterize the thermal stability of hexadecyltrimethylammonium bromide-modified montmorillonites prepared at different surfactant concentrations. Analysis by DSC shows that the molecular environment of the surfactant within the montmorillonite galleries is different from that in the bulk state. The endothermic peak at 70–100°C in the DTA curves of the modified montmorillonites is attributed to both the surfactant phase transformation and the loss of free and interlayer water. With an increase of surfactant-packing density, the amount of water residing in the modified montmorillonite decreases gradually, reflecting the improvement of the hydrophobic property for the organoclay. However, the increase in the surfactant packing density within the galleries leads to a decrease in the thermal stability of the organoclays.

With an increase of initial surfactant concentration for the preparation of organoclays, the surfactant- packing density increases gradually to a ‘saturated’ state. It was found that the cationic surfactant was introduced into the montmorillonite interlayer not only by cation exchange but also by physical adsorption.

Diffraction effects from interstratified phyllosilicates have been studied extensively, and several computer programs such as NEWMOD© are available to facilitate interpretation of X-ray diffraction (XRD) profiles. However, accurate quantification of samples containing multiple interstratified phyllosilicate minerals is difficult due to the generally subjective nature of interpretations. More recent automated fitting interpretations require extensive computational effort, involving numerous calculations of profiles with different fitting-parameter values. Computational cost in time per calculation is the key factor influencing the overall efficiency of automated profile fitting. In general, the matrix methodology developed by Kakinoki and Komura is more efficient than the NEWMOD© architecture. A new matrix methodology was developed that reduces the number of matrix operations such as multiplication and addition, and these modifications improve calculation efficiency by up to a factor of three, with even greater improvement for small crystallite sizes (< 20 layers). A new computer program, ClayStrat, based on the modified matrix methodology, was developed to calculate one-dimensional XRD profiles from interstratified phyllosilicates along the Z direction.

The ordering conformation of surfactant molecules in intercalated montmorillonite prepared at various concentrations was investigated by 13C MAS NMR. The 13C MAS NMR study demonstrates the coexistence of ordered and disordered chain conformations. Two main resonance peaks are associated with the backbone alkyl chains: the resonance at 33 ppm corresponds to the ordered conformation (all-trans), and the resonance at 30 ppm corresponds to the disordered conformation (mixture of trans and gauche). Deconvolution of 13C MAS NMR spectra indicates that the ordering conformation of surfactant molecules within the gallery of montmorillonite depends very much on their orientation and packing density. When amine chains are oriented parallel to the silicate layers, the amount of all-trans conformer decreases with the increase of amine concentration. However, the amount of all-trans conformer increases with the increase of amine concentration when amine chains radiate from the silicate layers. Furthermore, 13C MAS NMR spectra show that the intercalated surfactant molecules in the clay minerals never attained the complete liquidlike or solidlike behavior.

NEWMOD was developed by R.C. Reynolds, Jr., for the study of two-component interstratifications of clay minerals. One-dimensional X-ray diffraction (XRD) profiles of an interstratified system of two clay minerals can be simulated using NEWMOD, given a set of parameters that describes instrumental factors, the chemical composition of the system (e.g. the concentration of Fe and interlayer cations), and structural parameters (e.g. proportions of the two components, the nature of ordering, and crystallite size distribution). NEWMOD has served as the standard method for quantitatively evaluating interstratified clay minerals for >20 y. However, the efficiency and accuracy of quantitative analysis using NEWMOD have been limited by the graphical user interface (GUI), by the lack of quantitative measures of the goodness-of-fit between the experimental and simulated XRD patterns, and by inaccuracies in some structure models used in NEWMOD. To overcome these difficulties, NEWMOD+ was coded in Visual C++ using the NEWMOD architecture, incorporating recent progress in the structures of clay minerals into a more user-friendly GUI, greatly facilitating efficient and accurate fitting. Quantitative fitting parameters (unweighted R-factor, Rp, weighted R-factor, Rwp, expected R-factor, Rexp, and chisquare, χ2) are included, along with numerous other features such as a powerful series generator, which greatly simplifies the generation of multiple simulations and makes NEWMOD+ particularly valuable for teaching.

High-intensity vortex beams with tunable topological charges and low coherence are highly demanded in applications such as inertial confinement fusion (ICF) and optical communication. However, traditional optical vortices featuring nonuniform intensity distributions are dramatically restricted in application scenarios that require a high-intensity vortex beam owing to their ineffective amplification resulting from the intensity-dependent nonlinear effect. Here, a low-coherence perfect vortex beam (PVB) with a topological charge as high as 140 is realized based on the super-pixel wavefront-shaping technique. More importantly, a globally adaptive feedback algorithm (GAFA) is proposed to efficiently suppress the original intensity fluctuation and achieve a flat-top PVB with dramatically reduced beam speckle contrast. The GAFA-based flat-top PVB generation method can pave the way for high-intensity vortex beam generation, which is crucial for potential applications in ICF, laser processing, optical communication and optical trapping.

In the Spring of 2020, the onset of the global pandemic intensified existing inequalities, but also accelerated organizing within some of the most precarious economic sectors. The neoliberal university was no exception to this general trend, and from 2020 until 2022, student workers organized for union contracts, just pandemic responses, independent arbitration for harassment and improved conditions at their workplaces. In those years, while neoliberal universities issued empty calls for “community,” and a prompt return to normalcy, student workers mobilized themselves and won unprecedented gains from their institutions, rejecting administrative pleas for the defense of the status quo. The following “Report from the Field,” details the struggle of student workers organizing from 2020 to 2022 at the University of New Mexico, the University of Michigan, New York University, and Columbia University, and offers a collectively authored reflection on the challenges, victories and future concerns of its respective movements.

We present initial results from our JWST NIRSpec program to study the α-abundances in the M31 disk. The Milky Way has two chemically-defined disks, the low-α and high-α disks, which are closely related to the thin and thick disks, respectively. The origin of the two populations and the α-bimodality between them is not entirely clear, although there are now several models that can reproduce the observed features. To help constrain the models and discern the origin, we have undertaken a study of the chemical abundances of the M31 disk using JWST NIRSpec, in order to determine whether stars in M31’s disk also show an α-abundance bimodality. Approximately 100 stars were observed in our single NIRSpec field at a projected distance of 18 kpc from the M31 center. The 1-D extracted spectra have an average signal-to-noise ratio of 85 leading to statistical metallicity precision of 0.016 dex, α-abundance precision of 0.012 dex, and a radial velocity precision 8 km s-1 (mostly from systematics). The initial results indicate that, in contrast to the Milky Way, there is no α-bimodality in the M31 disk, and no low-α sequence. The entire stellar population falls along a single chemical sequence very similar to the MW’s high-α component which had a high star formation rate. While this is somewhat unexpected, the result is not that surprising based on other studies that found the M31 disk has a larger velocity dispersion than the MW and is dominated by a thick component. M31 has had a more active accretion and merger history than the MW which might explain the chemical differences.

Some consider potatoes to be unhealthy vegetables that may contribute to adverse cardiometabolic health outcomes. We evaluated the association between potato consumption (including fried and non-fried types) and three key cardiometabolic outcomes among middle-aged and older adults in the Framingham Offspring Study. We included 2523 subjects ≥30 years of age with available dietary data from 3-d food records. Cox-proportional hazards models were used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for hypertension, type 2 diabetes or impaired fasting glucose (T2DM/IFG), and elevated triglycerides, adjusting for anthropometric, demographic and lifestyle factors. In the present study, 36 % of potatoes consumed were baked, 28 % fried, 14 % mashed, 9 % boiled and the rest cooked in other ways. Overall, higher total potato intake (≥4 v. <1 cup-equivalents/week) was not associated with risks of T2DM/IFG (HR 0⋅97, 95 % CI 0⋅81, 1⋅15), hypertension (HR 0⋅95; 95 % CI 0⋅80, 1⋅12) or elevated triglycerides (HR 0⋅99, 95 % CI 0⋅86, 1⋅13). Stratified analyses were used to evaluate effect modification by physical activity levels and red meat consumption, and in those analyses, there were no adverse effects of potato intake. However, when combined with higher levels of physical activity, greater consumption of fried potatoes was associated with a 24 % lower risk (95 % CI 0⋅60, 0⋅96) of T2DM/IFG, and in combination with lower red meat consumption, higher fried potato intake was associated with a 26 % lower risk (95 % CI 0⋅56, 0⋅99) of elevated triglycerides. In this prospective cohort, there was no adverse association between fried or non-fried potato consumption and risks of T2DM/IFG, hypertension or elevated triglycerides.