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We study motility-induced phase separation in symmetric and asymmetric active binary mixtures. We start with the coarse-grained run-and-tumble bacterial model that provides evolution equations for the density fields ρ i ( r ⃗ , t). Next, we study the phase separation dynamics by solving the evolution equations using the Euler discretization technique. We characterize the morphology of domains by calculating the equal-time correlation function C(r, t) and the structure factor S(k, t), both of which show dynamical scaling. The form of the scaling functions depends on the mixture composition and the relative activity of the species, Δ. For k → ∞, S(k, t) follows Porod's law: S(k, t) ∼ k−(d+1) and the average domain size L(t) shows a diffusive growth as L(t) ∼ t1/3 for all mixtures. [ABSTRACT FROM AUTHOR]

Policy-guided Monte Carlo is an adaptive method to simulate classical interacting systems. It adjusts the proposal distribution of the Metropolis–Hastings algorithm to maximize the sampling efficiency, using a formalism inspired by reinforcement learning. In this work, we first extend the policy-guided method to deal with a general state space, comprising, for instance, both discrete and continuous degrees of freedom, and then apply it to a few paradigmatic models of glass-forming mixtures. We assess the efficiency of a set of physically inspired moves whose proposal distributions are optimized through on-policy learning. Compared to conventional Monte Carlo methods, the optimized proposals are two orders of magnitude faster for an additive soft sphere mixture but yield a much more limited speed-up for the well-studied Kob–Andersen model. We discuss the current limitations of the method and suggest possible ways to improve it. [ABSTRACT FROM AUTHOR]

The phase separation of protein and RNA mixtures underpins the assembly and regulation of numerous membraneless organelles in cells. The ubiquity of protein–RNA condensates in cellular regulatory processes is in part due to their sensitivity to RNA concentration, which affects their physical properties and stability. Recent experiments with poly-cationic peptide–RNA mixtures have revealed closed-loop phase diagrams featuring lower and upper critical solution temperatures. These diagrams indicate reentrant phase transitions shaped by biomolecular interactions and entropic forces such as solvent and ion reorganization. We employed atomistic simulations to study mixtures with various RNA–polylysine stoichiometries and temperatures to elucidate the microscopic driving forces behind reentrant phase transitions in protein–RNA mixtures. Our findings reveal an intricate interplay between hydration, ion condensation, and specific RNA–polylysine hydrogen bonding, resulting in distinct stoichiometry-dependent phase equilibria governing stabilities and structures of the condensate phase. Our simulations show that reentrant transitions are accompanied by desolvation around the phosphate groups of RNA, with increased contacts between phosphate and lysine side chains. In RNA-rich systems at lower temperatures, RNA molecules can form an extensive pi-stacking and hydrogen bond network, leading to percolation. In protein-rich systems, no such percolation-induced transitions are observed. Furthermore, we assessed the performance of three prominent water force fields—Optimal Point Charge (OPC), TIP4P-2005, and TIP4P-D—in capturing reentrant phase transitions. OPC provided a superior balance of interactions, enabling effective capture of reentrant transitions and accurate characterization of changes in solvent reorganization. This study offers atomistic insights into the nature of reentrant phase transitions using simple model peptide and nucleotide mixtures. We believe that our results are broadly applicable to larger classes of peptide–RNA mixtures exhibiting reentrant phase transitions. [ABSTRACT FROM AUTHOR]

Multicomponent macromolecular mixtures often form higher-order structures, which may display non-ideal mixing and aging behaviors. In this work, we first propose a minimal model of a quaternary system that takes into account the formation of a complex via a chemical reaction involving two macromolecular species; the complex may then phase separate from the buffer and undergo a further transition into a gel-like state. We subsequently investigate how physical parameters such as molecular size, stoichiometric coefficients, equilibrium constants, and interaction parameters affect the phase behavior of the mixture and its propensity to undergo aging via gelation. In addition, we analyze the thermodynamic stability of the system and identify the spinodal regions and their overlap with gelation boundaries. The approach developed in this work can be readily generalized to study systems with an arbitrary number of components. More broadly, it provides a physically based starting point for the investigation of the kinetics of the coupled complex formation, phase separation, and gelation processes in spatially extended systems. [ABSTRACT FROM AUTHOR]

Experimental and numerical studies were performed on the vibrational energy relaxation in shock-heated CO/N2/Ar mixtures. A laser absorption technique was applied to the time-dependent rovibrational temperature time-history measurements. The vibrational relaxation data of reflected-shock-heated CO were summarized at 1720–3230 K. In shock-tube experiments, the rotational temperature of CO quickly reached equilibrium, whereas a relaxation process was found in the time-dependent vibrational temperature. For the mixture with 1.0% CO and 10.0% N2, the vibrational excitation caused a decrease in the macroscopic thermodynamic temperature of the test gas. In the simulations, the state-to-state (StS) approach was employed, where the vibrational energy levels of CO and N2 are treated as pseudo-species. The vibrational state-specific inelastic rate coefficients of N2–Ar collisions were calculated using the mixed quantum–classical method based on a newly developed three-dimensional potential energy surface. The StS predictions agreed well with the measurements, whereas deviations were found between the Schwartz–Slawsky–Herzfeld formula predictions and the measurements. The Millikan–White vibrational relaxation data of the N2–Ar system were found to have the most significant impact on the model predictions via sensitivity analysis. The vibrational relaxation data of the N2–Ar system were then modified according to the experimental data and StS results, providing an indirect way to optimize the vibrational relaxation data of a specific system. Moreover, the vibrational distribution functions of CO and N2 and the effects of the vibration–vibration–translation energy transfer path on the thermal nonequilibrium behaviors were highlighted. [ABSTRACT FROM AUTHOR]

BACKGROUND: A growing literature suggests associations between occupational pesticide exposure and respiratory health. In this study, we aimed to examine the association of exposure to insecticides, fungicides, and herbicides, individually and as a mixture, with respiratory health outcomes and rhinitis in avocado farmworkers from Michoacán, Mexico. MATERIAL AND METHODS: We conducted a cross-sectional study of 105 avocado farmworkers between May and August 2021. We quantified 12 insecticide, fungicide, and herbicide metabolites in urine samples collected during two study visits (8-10 weeks apart). We collected survey data on self-reported pesticide use during the 12 months prior to the baseline survey and estimated annual exposure-intensity scores (EIS) using a semi-quantitative exposure algorithm. We also assessed respiratory symptoms, including wheezing, chest tightness, wheezing after exercise, and night cough. We used generalized linear regression models to examine associations of individual urinary metabolite concentrations and annual EIS with respiratory health outcomes and rhinitis. Mixture effects were assessed using Bayesian Weighted Quantile Sum (BWQS) regression. RESULTS: After adjusting for multiple comparisons, we observed mostly null associations of individual pesticide metabolite concentrations and annual EIS with the outcomes of interest. However, in BWQS analyses, we found evidence of a mixture association of urinary pesticide metabolites with increased odds of night cough (OR: 5.34, 95 % CrI: 1.67, 20.62). Pyrethroid metabolites 3-phenoxybenzoic acid and cis- and trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropanecarboxylic acid were the main contributors to this association (43 %). CONCLUSIONS: Our findings indicate that exposure to a mixture of pesticides, particularly pyrethroid insecticides, may be associated with night cough in avocado farmworkers.

Potential applications of previously synthesized pillared graphene oxide frameworks with phenyldiboronic acid linkers in the field of the adsorption and separation of polar protic and aprotic liquid solvents have been systematically explored using grand canonical Monte Carlo simulations. Particular attention was initially paid to the adsorption of pure liquid water, methanol, and dimethyl sulfoxide. The results obtained a significant increase in the isosteric heat of adsorption at low uptake in the case of dimethyl sulfoxide, which is about 17.9 and 26.8 kJ/mol higher than the values corresponding to methanol and water adsorption. These findings indicated that from a thermodynamic point of view, these pillared graphene oxide frameworks could be used in the separation of dimethyl sulfoxide–water liquid mixtures. Systematic grand canonical Monte Carlo simulations were then subsequently performed for dimethyl sulfoxide–water mixtures, with a low dimethyl sulfoxide concentration. The calculated values of the separation selectivity indicate that these materials could have potential applications in the separation of these mixed liquid solvents. Molecular dynamics simulations performed for a representative adsorbed mixture have revealed a substantial slowing down of the dynamics under confinement, particularly in the case of the hydrogen bonds formed between water and dimethyl sulfoxide. [ABSTRACT FROM AUTHOR]

Coarse-grained (CG) molecular models greatly reduce the computational cost of simulations allowing for longer and larger simulations, but come with an artificially increased acceleration of the dynamics when compared to the parent atomistic (AA) simulation. This impedes their use for the quantitative study of dynamical properties. During coarse-graining, grouping several atoms into one CG bead not only reduces the number of degrees of freedom but also reduces the roughness on the molecular surfaces, leading to the acceleration of dynamics. The RoughMob approach [M. K. Meinel and F. Müller-Plathe, J. Phys. Chem. B 126(20), 3737–3747 (2022)] quantifies this change in geometry and correlates it to the acceleration by making use of four so-called roughness volumes. This method was developed using simple one-bead CG models of a set of hydrocarbon liquids. Potentials for pure components are derived by the structure-based iterative Boltzmann inversion. In this paper, we find that, for binary mixtures of simple hydrocarbons, it is sufficient to use simple averaging rules to calculate the roughness volumes in mixtures from the roughness volumes of pure components and add a correction term quadratic in the concentration without the need to perform any calculation on AA or CG trajectories of the mixtures themselves. The acceleration factors of binary diffusion coefficients and both self-diffusion coefficients show a large dependence on the overall acceleration of the system and can be predicted a priori without the need for any AA simulations within a percentage error margin, which is comparable to routine measurement accuracies. Only if a qualitatively accurate description of the concentration dependence of the binary diffusion coefficient is desired, very few additional simulations of the pure components and the equimolar mixture are required. [ABSTRACT FROM AUTHOR]

In recent years, interest in synthetic C4F7N as a gas insulator has been growing due to its unique insulation properties and low global warming potential. In spite of this, very few studies are devoted to the analysis of the electric breakdown of C4F7N and its mixtures with other dilutants such as CO2 and N2. In the present paper, we use a two-dimensional fluid model to analyze the electrical breakdown of the atmospheric pressure C4F7N/N2 mixture. We establish the influence of the C4F7N fraction in the mixture and the cathode voltage rise rate on the breakdown voltage. We find that the ratio between the electron attachment frequency and the voltage rise rate defines the streamer parameters. Namely, if the time scale of electron attachment to C4F7N is much faster than the voltage rise rate, the plasma electronegativity of the streamer body and of its head is extremely high, and it is difficult to define exactly the streamer head location. In the opposite case of the fast rise rates, the conventional streamers with sharp heads were obtained. [ABSTRACT FROM AUTHOR]

A three-temperature collisional-radiative model for shock-heated nitrogen–argon mixtures is developed to facilitate the study of nonequilibrium electronic excitation and ionization behind strong shock waves. Model predictions accurately reproduce measurements of N 2 dissociation for mixtures of 2%–10% N 2 in argon, with some discrepancies observed for 20% N 2 mixtures. Potential causes of the discrepancies are discussed. Net dissociation in mixtures containing 20% N 2 is significantly impacted by the dissociation of N 2 (A), the first excited electronic state of N 2 , indicating that molecular electronic excitation can affect net dissociation in shock-heated nitrogen flows. The collisional-radiative model successfully predicts the three-stage behavior and induction time observed in concentration measurements of atomic nitrogen in its fourth excited state, the 3 s 4 P level, behind reflected shocks. Mechanisms for the observed behavior are discussed, which deviate from those inferred using a simpler kinetic model. Excited state number density predictions are strongly influenced by the modeling of radiation self-absorption and the inclusion of the measured non-ideal pressure rise. At higher N 2 concentrations, the measured data indicate increased efficiency of atomic nitrogen electronic excitation in collisions with N as compared to collisions with N 2 and Ar. A global sensitivity analysis of the excited state predictions is then performed, identifying the processes in the kinetic model that most sensitively influence the predicted excited state time history and further clarifying the dominant mechanisms affecting the experimental observables. [ABSTRACT FROM AUTHOR]

BACKGROUND: Motor function is critical for childrens health, yet remains an understudied neurodevelopmental domain. Exposure to metals has been linked with motor function, but no study has examined the joint effects of metal mixtures. METHODS: We evaluated cross-sectional associations between a metal mixture and motor function among 569 adolescents (10-14 years old) living near the ferroalloy industry. Concentrations of blood lead, hair manganese, hair copper, and hair chromium were quantified using inductively coupled plasma mass spectrometry. Neuropsychologists administered multiple fine motor function assessments: pursuit aiming, finger tapping, visual reaction time (VRT), and subtests from the Luria Nebraska battery. We estimated associations between motor function and the metal mixture using quantile-based g-computation and multivariable linear regression, adjusting for child age, sex, and socioeconomic status. We explored sex-specific associations in stratified models. RESULTS: Associations between the metal mixture and motor function were mostly null but were modified by sex. We observed a beneficial association among females: a quartile increase in all metals in the mixture was associated with a 2.6% faster average response time on the VRT (95% confidence interval [CI] = -4.7%, -0.5%), driven by Cu and Cr. In contrast, this association was adverse among males (ß = 1.5% slower response time [95% CI = -0.7%, 3.9%]), driven by Cu and Mn. CONCLUSIONS: Results suggest that males may be more susceptible to the adverse effects of metal exposure on motor function during adolescence than females. Future studies, particularly prospective study designs, are warranted to further understand the associations of metal mixtures with motor function.

In this study, we used a high-throughput computational screening approach to examine the potential of metal–organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum–temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10 Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents. [ABSTRACT FROM AUTHOR]

Prenatal per- and poly-fluoroalkyl substances (PFAS) exposure may influence gestational outcomes through bioactive lipids─metabolic and inflammation pathway indicators. We estimated associations between prenatal PFAS exposure and bioactive lipids, measuring 12 serum PFAS and 50 plasma bioactive lipids in 414 pregnant women (median 17.4 weeks' gestation) from three Environmental influences on Child Health Outcomes Program cohorts. Pairwise association estimates across cohorts were obtained through linear mixed models and meta-analysis, adjusting the former for false discovery rates. Associations between the PFAS mixture and bioactive lipids were estimated using quantile g-computation. Pairwise analyses revealed bioactive lipid levels associated with PFDeA, PFNA, PFOA, and PFUdA (p < 0.05) across three enzymatic pathways (cyclooxygenase, cytochrome p450, lipoxygenase) in at least one combined cohort analysis, and PFOA and PFUdA (q < 0.2) in one linear mixed model. The strongest signature revealed doubling in PFOA corresponding with PGD2 (cyclooxygenase pathway; +24.3%, 95% CI: 7.3-43.9%) in the combined cohort. Mixture analysis revealed nine positive associations across all pathways with the PFAS mixture, the strongest signature indicating a quartile increase in the PFAS mixture associated with PGD2 (+34%, 95% CI: 8-66%), primarily driven by PFOS. Bioactive lipids emerged as prenatal PFAS exposure biomarkers, deepening insights into PFAS' influence on pregnancy outcomes.

Structural and mechanical properties of membranes such as thickness, tail order, bending modulus and curvature energetics play crucial role in controlling various cellular functions that depend on the local lipid organization and membrane reshaping. While behavior of these biophysical properties are well understood in single component membranes, very little is known about how do they change in the mixed lipid membranes. Often various properties of the mixed lipid bilayers are assumed to change linearly with the mole fractions of the constituent lipids which, however, is true for "ideal" mixing only. In this study, using molecular dynamics simulations, we show that structural and mechanical properties of binary lipid mixture change nonlinearly with the lipid mole fractions, and the strength of the nonlinearity depends on two factors - spontaneous curvature difference and locally inhomogeneous interactions between the lipid components. [ABSTRACT FROM AUTHOR]

1-propanol/water mixtures over the whole composition range (0 < XV ≤ 1; XV is the 1-propanol volume fraction) are shown to be structurally and dynamically heterogeneous. By combining structural (x-ray diffraction), thermodynamic (differential scanning calorimetry) and dynamical probes (dielectric spectroscopy) we construct the pertinent phase diagram. It consists of liquid 1-propanol, liquid water, hexagonal ice and different hydrates, the latter sharing the same lattice. The phase diagram can be discussed in terms of four regimes, all having in common a droplet arrangement of the minority component. When water droplets are strongly confined by 1-propanol (regime I, 0.92 < XV ≤ 1; "soft" confinement), water is unable to crystallize. It has dynamics reminiscent to the ultra-viscous water phase known as high-density liquid (HDL). When water droplets are moderately confined (regime II, 0.75 < XV ≤ 0.92) water can crystallize via homogeneous nucleation. Strikingly, the homogeneous nucleation temperature is at 205 K, well within "no-man's land." The result is in line with earlier reports that soft confinement is the key to enter into the "no-man's land". When 1-propanol is the minority component (regimes III and IV), the structure and the dynamics are dominated by the 1-propanol/water interface with the formation of hydrates. The corresponding dynamical features suggest a link between hydrate formation and the two metastable phases of ultra-viscous water, HDL and low-density liquid. [ABSTRACT FROM AUTHOR]

Effective "soft" interactions between macromolecules such as polymers, amphiphilic dendrimers, and suitably designed DNA based dendritic molecules have been shown to be purely repulsive and non-diverging. We report the structure and phase behavior of a mixture of hard colloids and soft coarse-grained macromolecules. Through the use of Reference Interaction Site Model theory and molecular dynamics simulations we find that hard colloids and soft macromolecules act as depletants toward each other, generating a medium-induced effective attraction. This effective attraction leads to the formation of non-dispersed phases at high densities. At low and high fractions of hard colloids the system macrophase separates into two disparate regions of hard colloids and soft macromolecules. However, this system microphase separates into a hard-rich and soft-rich self-assembled domains at intermediate compositions. The formation of microphase separated structure in this system of isotropic, disconnected, and purely repulsive colloids is surprising and quite novel. This behavior is likely due to a softening of the interface between hard-rich and soft-rich self-assembled domains. Molecular dynamics simulations have revealed that the microphase separated state has an overall disordered bicontinuous morphology. The hard-rich domain forms an ordered FCC structure and the soft-rich domain forms a disordered cluster-fluid, making the structure simultaneously ordered and disordered. [ABSTRACT FROM AUTHOR]

Coarse-grained (CG) simulation models of condensed-phase systems can be derived with well-established methods that perform coarse-graining in space and provide an effective Hamiltonian with which some of the structural and thermodynamic properties of the underlying fine-grained (FG) reference system can be represented. Coarse-graining in time potentially provides CG models that furthermore represent dynamic properties. However, systematic efforts in this direction have so far been limited, especially for moderately coarse-grained, chemistry-specific systems with complicated conservative interactions. With the aim of representing structural, thermodynamic, and dynamic properties in CG simulations of multi-component molecular systems, we investigated a recently introduced method in which the force on a CG particle originates from conservative interactions with surrounding particles and non-Markovian dissipative interactions, the latter introduced by means of a colored-noise thermostat. We examined two different methods to derive isotropic memory kernels required for integrating the corresponding generalized Langevin equation (GLE) of motion, based on the orthogonal dynamics of the FG forces and on an iterative optimization scheme. As a proof of concept, we coarse-grain single-component molecular liquids (cyclohexane, tetrachloromethane) and ideal and non-ideal binary mixtures of cyclohexane/tetrachloromethane and ethanol/tetrachloromethane, respectively. We find that for all systems, the FG single particle velocity auto-correlation functions and, consequently, both the short time and long time diffusion coefficients can be quantitatively reproduced with the CG-GLE models. We furthermore demonstrate that the present GLE-approach leads to an improved description of the rate with which the spatial correlations decay, which is artificially accelerated in the absence of dissipation. [ABSTRACT FROM AUTHOR]

BackgroundA growing body of literature investigated childhood exposure to environmental chemicals in association with attention-deficit/hyperactivity disorder (ADHD) symptoms, but limited studies considered urinary mixtures of multiple chemical classes. This study examined associations of concurrent exposure to non-persistent chemicals with ADHD symptoms in children diagnosed with autism spectrum disorder (ASD), developmental delay (DD), and typical development (TD).MethodsA total of 549 children aged 2-5 years from the Childhood Autism Risks from Genetics and Environment (CHARGE) case-control study were administered the Aberrant Behavior Checklist (ABC). This study focused on the ADHD/noncompliance subscale and its two subdomains (hyperactivity/impulsivity, inattention). Sixty-two chemicals from four classes (phenols/parabens, phthalates, organophosphate pesticides, trace elements) were quantified in child urine samples, and 43 chemicals detected in > 70% samples were used to investigate their associations with ADHD symptoms. Negative binomial regression was used for single-chemical analysis, and weighted quantile sum regression with repeated holdout validation was applied for mixture analysis for each chemical class and all chemicals. The mixture analyses were further stratified by diagnostic group.ResultsA phthalate metabolite mixture was associated with higher ADHD/noncompliance scores (median count ratio [CR] = 1.10; 2.5th, 97.5th percentile: 1.00, 1.21), especially hyperactivity/impulsivity (median CR = 1.09; 2.5th, 97.5th percentile: 1.00, 1.25). The possible contributors to these mixture effects were di-2-ethylhexyl phthalate (DEHP) metabolites and mono-2-heptyl phthalate (MHPP). These associations were likely driven by children with ASD as these were observed among children with ASD, but not among TD or those with DD. Additionally, among children with ASD, a mixture of all chemicals was associated with ADHD/noncompliance and hyperactivity/impulsivity, and possible contributors were 3,4-dihydroxy benzoic acid, DEHP metabolites, MHPP, mono-n-butyl phthalate, and cadmium.ConclusionsEarly childhood exposure to a phthalate mixture was associated with ADHD symptoms, particularly among children with ASD. While the diverse diagnostic profiles limited generalizability, our findings suggest a potential link between phthalate exposure and the comorbidity of ASD and ADHD.

We consider a dissipative Baer-Nunziato type system for a mixture of two compressible heat conducting gases in the whole space. The existence theory of the global solution to the system is established in H N (R 3) -framework (N ≥ 2) when only the H 2 -norm of the initial perturbation is small. The weighted energy method combined with the low-frequency and high-frequency decomposition is used to derive the desired a priori estimates and hence the global existence. As a by-product, we obtain the decay rates of spatial derivatives of the solution. [ABSTRACT FROM AUTHOR]

A catalyst-free method was developed for the ring opening of azlactones (also known as oxazolones) in water microdroplets. Azlactone was dissolved in a water : acetonitrile (1 : 1) mixture, and the solution is sprayed by using nitrogen gas at a pressure of 120 psi to generate microdroplets. This method promoted selective cleavage of the lactone bond to afford the corresponding N-benzoyl derivatives in up to 94% isolated yield with no epimerization. Our method produces the ring-opening products in milliseconds (up to 94 μmol for 33.3 minutes), and may have utility for high-throughput synthesis applications. [ABSTRACT FROM AUTHOR]

Donor–acceptor systems for CO2 activation combining a formally zero-valent group 6 metal as the donor with the Lewis acid Al(C6F5)3 (AlCF) are reported. They were obtained from AlCF adducts of N2-complexes by N2-to-CO2 substitution. One species was capable of C–O cleavage. The boron analogues led to intractable mixtures. [ABSTRACT FROM AUTHOR]

The K-optimality criterion is proposed to avoid multicollinearity in regression analysis. By far the most, popular models for modeling the response of a mixture experiment are the Scheffé polynomial models. The Scheffé polynomial models have a small degree of multicollinearity. However, there have been no reports about constructing K-optimal designs for the Scheffé polynomial models. This article expands the K-optimality criterion to the second-order Scheffé polynomial model, and derives the K-optimal allocations for such model. We also investigate the construction method of K-optimal designs with the non linear constraints. In addition, the relative efficiencies of D-, A-, and K-optimal designs are compared. [ABSTRACT FROM AUTHOR]

Data are heterogeneous when recorded in different time regimes or taken from multiple sources to some degree. Varying-coefficient models or mixture models are suitable for solving this type of problem. On one hand, existing models are quite complicated and computationally cumbersome especially for large-scale data. On the other hand, common effects among different data sources are unknown. Additionally, some existing models are unable to search the non linear relationship between response and covariates. To address these challenges, we aim at estimating common effects about non parametric regression when data are heterogeneous. Our proposed estimation method is based on basis function expansion. Adaptive basis series and fixed basis series are considered, respectively. We exploit maximin aggregation technique to get a simple non linear model, also the common effects, from all possible grouped data. The mean squared error and asymptotic distribution of the estimator are investigated. Simulation studies and real-data analysis are conducted to verify the efficiency of the estimation procedure. Comparing with ordinary least square estimator and averaging ordinary least square estimator, our proposed estimator can reduce the complexity of data sources and is more robust. [ABSTRACT FROM AUTHOR]

In this article, we give a unified method to derive the classical characteristic functions of all elliptical and related distributions in terms of Bessel functions. The approach is based on the stochastic representation of an elliptical random variable and the characteristic function of uniform distribution on the unit sphere surface in ℝn. In particular, we present the simple closed form of characteristic functions for commonly used distributions such as multivariate t, Pearson Type II, Pearson Type VII, Kotz type, and Bessel distributions. Some extensions are also being investigated. [ABSTRACT FROM AUTHOR]

Purification of C2H4 from the ternary C2 hydrocarbon mixture in one step is of critical significance but still extremely challenging according to its intermediate physical properties between C2H6 and C2H2. Hydrogen‐bonded organic frameworks (HOFs) stabilized by supramolecular interactions are emerging as a new kind of adsorbents that facilitate green separation. However, it remains a problem to efficiently realize the one‐step C2H4 purification from C2H6/C2H4/C2H2 mixture because of the low C2H2/C2H4 selectivity. We herein report a robust microporous HOF (termed as HOF‐TDCPB) with dense O atoms and aromatic rings distributed on the pore surface which provide C2H6 and C2H2 preferred environment simultaneously. Dynamic breakthrough experiments indicate that HOF‐TDCPB can not only obtain high‐purity C2H4 from binary C2 mixture, but also firstly realize one‐step C2H4 purification from ternary C2H6/C2H4/C2H2 mixture, with the C2H4 productivity of 3.2 L/kg (>99.999 %) for one breakthrough cycle. Furthermore, HOF‐TDCPB displays outstanding stability in air, organic solvents and water, which endow it excellent cycle performance even under high‐humidity conditions. Theoretical calculations indicate that multiple O sites on pore channels can create synergistic binding sites for C2H2, thus affording overall stronger multipoint interactions. [ABSTRACT FROM AUTHOR]

In this work, ZrW2O8‐coated ZrC composite powders are synthesized by solid‐state reaction method using ZrC and WO3 powders. Thermodynamic analysis shows that when the molar ratio of ZrC to WO3 is larger than 5:4, ZrW2O8 cannot be synthesized by solid reaction of ZrC and WO3. The favorable molar ratio of ZrC to WO3 for solid reaction synthesis ZrW2O8 is 1:2. After reacted below 800°C for 8 hours, only ZrC in the ZrC and WO3 mixture powders partially reacts with oxygen to form ZrO2. And there is no detectable reaction between WO3 and the formed ZrO2 to produce ZrW2O8. ZrC and WO3 can synthesize ZrW2O8 at 900°C. ZrW2O8‐coated ZrC composite powders can be synthesized using powder mixtures with molar ratio of ZrC:WO3 = 1:1.7 and ZrC:WO3 = 1:1.9 after heat treatment at 1000°C for 4 hours. The synthesized ZrW2O8‐coated ZrC particles show cubic shape with obvious particles growth. The exothermic oxidation reaction of ZrC leads to a significant increase in local temperature, which is believed to trigger partial reaction between ZrO2 and WO3 to form ZrW2O8. [ABSTRACT FROM AUTHOR]

Key points Decreased overall dietary consumption of micronutrients may be linked to an increased risk of olfactory dysfunction (OD) including subjective report of OD, subjective report of phantosmia, and objective OD. Interactions were identified between these micronutrients, suggesting that outcomes may vary depending on the mixture of micronutrients taken. [ABSTRACT FROM AUTHOR]

Compared with pure NH 3 fuel, the lower NO emission conditions of NH 3 –H 2 mixtures under the oxygen-enriched combustion mode have been identified quantitatively. Furthermore, the effects of the H 2 addition on the NO productions of premixed oxygen-enriched NH 3 –H 2 flames are studied numerically, while the major reactions responsible for the variation of total NO are identified. Results show that the H 2 addition is eligible to reduce the NO emissions of the oxygen-enriched NH 3 combustion if the laminar burning velocity is fixed to a larger value (>23 cm/s). The quantitative equations are obtained to determine the optimum oxygen-enriched conditions of the NH 3 –H 2 mixture, aiming to achieve lower NO emission and similar or improved combustion stability compared to pure NH 3 fuel by restricting the minimum and maximum O 2 percentages for the NH 3 –H 2 mixtures. Based on the rate of production (ROP) analysis, for the oxygen-enriched NH 3 –H 2 combustion, R144 (HNO + H<=>H 2 +NO) is consistently the most significant NO production reaction, while R85 (NH + NO<=>N 2 O + H) and R91 (N + NO<=>O + N 2) play significant roles in the NO consumption. When the laminar burning velocity (S L) is kept to a lower value, the increased total NO of the oxygen-enriched NH 3 flames with the H 2 addition is ascribed to more efficient suppressions on the NO consumption reactions of R85, R91 and R77 (NH 2 +NO<=>NNH + OH). In contrast, thanks to the extra impact of the higher O 2 percentage on the H/O/OH radical pool at larger S L , the NO production reactions begin to suffer stronger suppressions of the H 2 addition, resulting in the reduced total NO of NH 3 –H 2 mixtures. Furthermore, R144 is identified as the key reaction influencing the variation trend of total NO at both lower and higher S L values. • NO emissions of oxygen-enriched NH 3 –H 2 combustion are investigated. • Lower NO emission conditions of NH 3 –H 2 mixture than NH 3 are identified. • H 2 addition leads to opposite change of NO emission at small and large S L. • Effects of H 2 addition on NO formations are analyzed at different S L. • R144 plays a decisive role in determining the opposite change of NO emission. [ABSTRACT FROM AUTHOR]

Although the normal distribution is the most frequently used distribution for modeling a given data in many applications due to its desirable theoretical properties and computational convenience, it is often not suitable to model the data having asymmetric or heavy tailed distributions. The skew-normal distribution is an important alternative to the normal distribution as it can cover not only the normal distribution but also some asymmetric distributions. However, it cannot well approximate heavy tailed distributions. In this paper, we propose a semiparametric skew-normal distribution which contains skew-normal distributions using the nonparametric scale mixture of skew-normal distributions and apply the proposed model to finite mixture models so that we can obtain more efficient and insightful knowledge in the model-based cluster analysis. We provide a feasible algorithm to compute all parametric and nonparametric components in the proposed model. Numerical examples to show the applicability of the proposed model are also presented. [ABSTRACT FROM AUTHOR]

This study introduces a novel approach to estimate tail dependence in financial contagion using mixture copulas. Addressing the challenges of weight parameter estimation in conventional models, we propose a Bayesian model averaging method to determine optimal copula weights. Through both simulations and empirical studies, the proposed method demonstrates improved robustness and accuracy, particularly when handling extreme weight scenarios. These advancements offer more reliable measurements of financial contagion, contributing to enhanced risk management and policy-making in interconnected financial markets. [ABSTRACT FROM AUTHOR]

Owing to a lack of methodology for rationally and selectively synthesizing twisted nanographenes, it is usually inevitable that we obtain nanographenes as a mixture with various geometries, such as unidirectionally twisted, alternatively twisted, randomly twisted, and even wavy structures, reflecting the high activation barriers among them. Otherwise, they are interconvertible if the barriers are low enough such that only averaged properties can be observed under a thermal equilibrium. Recently, we reported on a double-twisted nanographene containing four [6]helicene units within the skeleton. In this paper, we discuss the robust conformational stability of the nanographene, both experimentally and computationally. The results indicate that the nanographene could only be racemized at temperatures exceeding 200 °C, and the first flip of one of the four [6]helicene units is the rate-degerming step. [ABSTRACT FROM AUTHOR]

In this study, a novel unit cell design is proposed, which eliminates the buckling tendency of the auxetic honeycomb. The novel unit cell design is a more balanced, diagonally reinforced doubly re-entrant auxetic honeycomb structure (x-reinforced auxetic honeycomb for short). We investigated and compared this novel unit cell design against a wide parameter range. Compression tests were carried out on specimens 3D-printed with a special, unique, flexible but tough resin mixture. The results showed that the additional, centrally pronounced reinforcements resulted in increased deformation stability; parameter-independent, non-buckling deformation behaviour is achieved; however, the novel structure is no longer auxetic. Mechanical properties, such as compression resistance and energy absorption capability, also increased significantly—An almost four times increase can be observed. In contrast to the deformation behaviour (which became predictable and constant), the mechanical properties can be precisely adjusted for the desired application. This novel structure was also investigated in a highly accurate, validated finite element environment, which showed that critical stress values are formed in well-supported regions, meaning that critical failure is unlikely. Our novel lattice unit cell design elevated the auxetic honeycomb to the realm of modern, high performance and widely applicable lattice structures. [ABSTRACT FROM AUTHOR]

In the last decades, many computational models have been developed to predict soft tissue growth and remodeling (G&R). The constrained mixture theory describes fundamental mechanobiological processes in soft tissue G&R and has been widely adopted in cardiovascular models of G&R. However, even after two decades of work, large organ‐scale models are rare, mainly due to high computational costs (model evaluation and memory consumption), especially in long‐range simulations. We propose two strategies to adaptively integrate history variables in constrained mixture models to enable large organ‐scale simulations of G&R. Both strategies exploit that the influence of deposited tissue on the current mixture decreases over time through degradation. One strategy is independent of external loading, allowing the estimation of the computational resources ahead of the simulation. The other adapts the history snapshots based on the local mechanobiological environment so that the additional integration errors can be controlled and kept negligibly small, even in G&R scenarios with severe perturbations. We analyze the adaptively integrated constrained mixture model on a tissue patch for a parameter study and show the performance under different G&R scenarios. To confirm that adaptive strategies enable large organ‐scale examples, we show simulations of different hypertension conditions with a real‐world example of a biventricular heart discretized with a finite element mesh. In our example, adaptive integrations sped up simulations by a factor of three and reduced memory requirements to one‐sixth. The reduction of the computational costs gets even more pronounced for simulations over longer periods. Adaptive integration of the history variables allows studying more finely resolved models and longer G&R periods while computational costs are drastically reduced and largely constant in time. [ABSTRACT FROM AUTHOR]

Productive grasslands in temperate regions have relied strongly on low plant diversity with high management intensity and fertiliser inputs. Increasing plant diversity can provide high yields of digestible forage for livestock production with lower environmental impacts, and thus represents a diversity‐dependent nature‐based solution that can deliver multiple ecosystem functions.Sharing lessons from the design of managed, productive grassland communities, we address the following questions: how can we identify combinations of plant species that best deliver a selected function or multiple functions? and; when is community composition more important than species richness?We describe approaches that separate plant diversity into its underlying components: species richness, composition and relative abundance. Disentangling these three components facilitates a more nuanced understanding of how diversity can contribute to the design of diversity‐dependent nature‐based solutions. [ABSTRACT FROM AUTHOR]

Depolarization dyadics were computed for superspheroidal particles made of an isotropic dielectric material and immersed in a uniaxial dielectric material. Superspheroidal shapes of two kinds were considered: one intermediate between spheroidal and cylindrical, and the other intermediate between spheroidal and cuboidal. These depolarization dyadics were employed in the Maxwell Garnett and Bruggeman homogenization formalisms to estimate the relative permittivity dyadics of homogenized composite materials (HCMs) that are random mixtures of identically oriented superspheroidal particles. The anisotropy of the HCMs was exposed through numerical investigations which revealed the dependencies of the HCM's anisotropy upon the shapes of the constituent particles and their volume fractions. The largest degrees of HCM anisotropy arose when the shape of the constituent particles deviated most from spherical, especially at mid-range volume fractions. Estimates of HCM anisotropy from the Maxwell Garnett and Bruggeman formalisms were broadly similar over the volume-fraction range appropriate for the Maxwell Garnett formalism, with modest differences being most apparent for particle shapes that deviated most from spherical. [ABSTRACT FROM AUTHOR]

ABSTRACT Hyphenated chromatographic techniques are widely used to analyze and characterize complex samples. Chemometric methods are generally needed to extract the qualitative and quantitative information of the target analytes from complex hyphenated chromatographic data. However, neither two‐way nor three‐way chemometric methods are efficient enough in analyzing hyphenated chromatographic data with both severe peak overlapping and retention time shift across samples. To address this issue, a practical framework was proposed herein. It consists of three chemometric algorithms, that is, (1) “fix‐sized moving window evolving target spectral projection” for locating the possible peak positions of the target analytes, (2) “target identification based on singular value comparison” for determining whether the identified peaks are indeed the chromatographic peaks of the target analytes, and (3) “fix‐sized moving window evolving trilinear decomposition” for obtaining the quantitative results of the target analytes. Experimental results on the GC‐MS data sets of mixture samples of 10 compounds verified that the proposed framework could deal with the problems of both severe peak overlapping and retention time shift across samples. The proposed framework has the advantages of simplicity in concept, easy implementation, and good performance and hence is expected to be a competitive alternative to existing methods for the analysis of hyphenated chromatographic data of complex samples. [ABSTRACT FROM AUTHOR]

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals known for their environmental persistence and resistance to biodegradation. This study investigated the impact of adolescent exposure to a PFAS mixture on adult ovarian function. Female CD-1 mice were orally exposed to vehicle control or a PFAS mixture (comprised of perfluorooctanoic acid, perfluorooctanesulfonic acid, undecafluoro-2-methyl-3-oxahexanoic acid, and perfluorobutanesulfonic acid) for 15 d. After a 42-d recovery period, reproductive hormones, ovarian fibrosis, and ovarian gene and protein expression were analyzed using ELISA, Picrosirius red staining, qPCR, and immunoblotting, respectively. Results revealed that PFAS exposure did not affect adult body or organ weight, although ovarian weight slightly decreased. PFAS-exposed mice exhibited a disturbed estrous cycle, with less time spent in proestrus than control mice. Follicle counting indicated a reduction in primordial and primary follicles. Serum analysis revealed no changes in steroid hormones, follicle-stimulating hormone, or anti-Müllerian hormone, but a significant increase in luteinizing hormone was observed in PFAS-treated mice. Ovaries collected from PFAS-treated mice had increased mRNA transcripts for steroidogenic enzymes and fatty acid synthesis-related genes. PFAS exposure also increased collagen content in the ovary. Additionally, serum tumor necrosis factor-α levels were higher in PFAS-treated mice. Finally, transcripts and protein abundance for Hippo pathway components were upregulated in the ovaries of the PFAS-treated mice. Overall, these findings suggest that adolescent exposure to PFAS can disrupt ovarian function in adulthood. [ABSTRACT FROM AUTHOR]

In this study it is approached a linear model for the mixture of two Cosserat bodies having pores. It is formulated the mixed problem with initial and boundary data in this context. The main goal is to show that the coefficients that realize the coupling of the elastic effect with the one due to voids can vary, without the mixture being essentially affected. In a more precise formulation, this means that a small variation of the coefficients in the constitutive equations of the two continua causes only a small variation of the solutions of the corresponding mixed problems, that is, the continuous dependence of the solutions in relation to these coefficients is ensured. The considered mixture model is consistent because all estimates, specific to continuous dependence, are made based on rigorous mathematical relationships. [ABSTRACT FROM AUTHOR]

In this paper, we prove the equidistribution property of high-frequency eigensections of the Laplacian on a certain series of unitary flat bundles, using the mixture of semiclassical and geometric quantizations. [ABSTRACT FROM AUTHOR]

Effect assessments of metals are mostly based on single‐metal, single‐species tests, thereby ignoring metal‐mixture effects and indirect effects through species interactions. We tested the combined effects of metal and species interactions in two‐trophic algal–daphnid microcosms. Metal‐mixture effects on daphnid communities may propagate from effects on the generally more sensitive algal communities. Four different algal communities (three species each), with and without addition of the same daphnid community (three species) were exposed to single metals and one metal mixture (17:17:51 µg/L Ni:Cu:Zn). Daphnid densities were negatively affected by metals in the two‐trophic test, the magnitude of which depended on the algal community composition. Algal densities were overall positively affected by the metals in the two‐trophic test but negatively in the single‐trophic test, illustrating an indirect positive effect in the two‐trophic system due to a reduced grazing pressure. Metal effects on daphnid communities in the two‐trophic test (day 21) were correlated with metal effects on the single‐trophic–level algal communities during exponential growth (R2 = 0.55, p = 0.0011). This finding suggests that metal effects propagate across trophic levels due to a reduced food quantity. However, the indirect positive effects on algal densities, resulting in abundant food quantity, suggests that metal effects can also propagate to daphnids due to a reduced food quality (not measured directly). Metal‐mixture interactions on daphnid densities varied during exposure, but were additive or antagonistic relative to independent action when final daphnid densities were considered (day 56). This suggests stronger indirect effects of the mixture compared with the single metals. Overall, our study highlights the dynamic aspect of community‐level effects, which empirical reference models such as independent action or concentration addition cannot predict. Environ Toxicol Chem 2024;43:2350–2364. © 2024 SETAC [ABSTRACT FROM AUTHOR]

This research aims to investigate the self-healing of low-temperature cracks in asphalt mixture using semicircular bending tests at different modes of fracture. In this research, samples are fabricated with a 12.5 mm nominal size aggregate and PG58-22 binder. All aged and unaged asphalt samples are subjected to 10 cooling cycles. Also, the resting time between cooling cycles is applied to self-healed samples. The results show that cooling cycles significantly reduce the fracture energy and applying the resting time increases the healing, cracking resistance, and balanced cracking indices. In addition, the most effective of self-healing is observed at fracture mode II. [ABSTRACT FROM AUTHOR]

The identification of sensing group targets and extended targets is of paramount importance in the context of vehicle tracking and early warning detection. As the scope of target monitoring and tracking extends, conventional single-sensor-based tracking techniques are proving to be inadequate in meeting the practical demands of the field. Consequently, multi-sensor fusion tracking technology has emerged as a viable alternative. However, the use of multiple sensors is constrained by their limited fields of view (FOVs), which leads to issues such as the loss of target detection and the introduction of false targets after fusion. Hence, this study proposes a combination of weighted geometric averaging (WGA) and weighted arithmetic averaging (WAA) methods to solve distributed multi-group/extended target tracking with different fields of view. Specifically, a local Poisson multi-Bernoulli mixture (PMBM) filter was first used on individual sensors. Subsequently, we combined a sequential fusion technique and the proposed fusion approach to fuse the PMBM filter densities. The efficacy and superiority of this approach were demonstrated through simulations. [ABSTRACT FROM AUTHOR]

The focus of this study is to use the mixture item response theory (MixIRT) model while implementing the no-U-turn sampler as a technique for investigating the presence of latent classes (i.e., subpopulations) among eighth-grade students who were administered TIMSS 2019 mathematics subtest in paper format from the gulf cooperation council (GCC) countries. One-, two-, and constrained three-parameter logistic MixIRT models with one to four classes were used to fit to the data, where the model data fit was assessed using Bayesian fit indices. The results indicate that multiple latent classes or subpopulations can better reflect the mathematical proficiency of eighth graders from the four GCC countries, and specifically the two-class constrained three-parameter MixIRT model provides a relatively better fit to the data. The results also indicate that when a mixture of several latent classes present, the conventional unidimensional IRT model is limited in providing information for multiple latent classes and shall be avoided. In addition to adding to the existing literature on MixIRT models for international large-scale assessments such as TIMSS on its heterogenous subpopulations from a fully Bayesian approach, this study sheds light on the limitation of conventional unidimensional IRT models and subsequently directs attention to the use of the more complex MixIRT model for such assessments. [ABSTRACT FROM AUTHOR]

The generation of surplus sludge during biological wastewater treatment has become a prevalent issue, necessitating the development of a dewatering approach that is efficient, economically feasible, and ecologically sound. Bdellovibrio-and-like-organisms (BALOs) are obligatory parasitic bacteria that prey on an array of bacteria. In this study, different BALO strains were isolated and purified from waste activited sludge (WAS). Anti-predation host strains were applied to screen the BALO strains with different host-range to minimize the overlap of the biolysis prey spectrum. In addition, the BALO strains with different host preferences were mixed for sludge biolysis treatment efficiency comparison. The results indicated that the capillary suction time and the bound water content in the WAS treated with the mixed BALOs were significantly decreased by 25.9% ± 1.7% and 5.2% ± 1.2%, respectively, compared to those treated with the single BALO strain. The soluble chemical oxygen demand concentration in the mixed BALOs treated group was increased by 31.2% ± 0.7% than that treated with the single strain. The findings indicate that the mixed strains used in the treatment process resulted in a notable enhancement of both sludge dewatering performance and lysis degree. In addition, the abundance of Proteobacteria treated with the BALO mixtures decreased by 69.1% than the single strain treated one which demonstrated that the BALO mixture expanded the sludge host lysis spectrum. This study revealed the different effects of single and mixed strains on sludge community structure, suggesting that the BALO host-range expansion is crucial to further improve sludge dewatering performances. [ABSTRACT FROM AUTHOR]

In this study, a new method was introduced to induce micellar transitions by using vesicles formed from mixed surfactants, which offer enhanced stability. Different physicochemical analysis methods were used to study the transition mechanism and the aggregation behavior of the mixed aqueous system composed of the double‐chain cationic didodecyldimethylammonium bromide (DDAB) and a single‐chain nonionic fluorinated surfactant undecafluoro n‐pentyl decaoxyethylene ether (C5F11(EO)10), by varying the fraction of DDAB, then the total surfactant concentration of DDAB/C5F11(EO)10 mixed system at XDDAB = 0.9. The obtained results indicated that the addition of the fluorinated surfactant C5F11(EO)10 to the mixed system resulted in a reduction of the surface tension (γ) and a decrease in the Electrical conductivity (K). Furthermore, even at high total concentrations of the mixed system, the conductivity and charge density at the surface remained stable. As XDDAB values increased, a higher degree of dissociation (α) was observed, along with negative values in the thermodynamic parameters of micellization (ΔGCMC°$$ {G}_{\mathrm{CMC}}^{{}^{\circ}} $$, ΔGCVC°$$ {G}_{\mathrm{CVC}}^{{}^{\circ}} $$, and ΔGads°$$ {G}_{\mathrm{ads}}^{{}^{\circ}} $$), confirming the transition from micelles to vesicles. The dynamic light scattering (DLS) analysis revealed the formation of two stable types of aggregates at both low and high concentrations, as supported by the zeta potential (ζ). Upon increasing the concentration of surfactants, UV–Vis absorption measurements indicated that small spherical micelles grow into large multilamellar vesicles, as evidenced by an increase in turbidity and confirmed transmission electron microscopy images. [ABSTRACT FROM AUTHOR]

AbstractThe traditional estimation of mixture regression models is based on the assumption of normal error components, making it susceptible to outliers or heavy-tailed errors. A new robust mixture regression model based on the symmetric α-stable (S α S) distribution, by extending the mixture of S α S distributions to the regression setting, is proposed. The S α S distribution is a heavy-tailed extension of the normal distribution, with the tails’ weight controlled by an additional parameter, α∈(0,2]. Generally, the variance of a S α S distribution diverges to infinity when α<2, and this allows the model to be more robust than competing heavy-tailed distributions such as the t-distribution when the degrees of freedom are larger than 2, which is advantageous because it allows robustness against the gross outliers in the data. The maximum likelihood estimates of the model parameters (except for α) are obtained using an expectation-maximization (EM) approach, and α is estimated via a stochastic EM based on a rejection sampling method. To demonstrate and contrast the proposal with other mixture regression models, real and simulated data are employed. [ABSTRACT FROM AUTHOR]

Background: The developing kidney is vulnerable to prenatal environmental factors such as metal exposure, potentially altering the risk of later-life kidney dysfunction. This study examines the relationship between prenatal metal exposures, individually and as mixtures, and adolescent kidney function in Project Viva, a prospective longitudinal birth cohort in Massachusetts, USA. Methods: We used data on metals measured in blood during pregnancy including 15 in the first trimester and four in the second trimester. We calculated estimated glomerular filtration rate (eGFR) in adolescents (mean: 17.7 years) using cystatin C- (eGFRcys) and creatinine-based (eGFRcreat) equations for children. We used linear regression for single metal analyses, and Bayesian kernel machine regression and quantile-based g-computation for mixture analyses, adjusting for relevant covariates. To account for multiple comparisons in the single metal analyses, we applied the Holm-Bonferroni procedure to control the false discovery rate. Results: This study included 371 participants with first trimester metals and adolescent eGFR, and 256 with second trimester metals. Each doubling in first trimester cadmium concentration was associated with lower adolescent eGFRcys (β:-1.51; 95% CI:-2.83, -0.18). Each doubling in first trimester chromium (β:-1.45; 95% CI:-2.71, -0.19), nickel (β:-1.91; 95% CI:-3.65, -0.16), and vanadium (β:-1.69; 95% CI:-3.21, -0.17) was associated with lower adolescent eGFRcreat. After adjusting for multiple comparisons, p-values for associations between adolescent eGFR and chromium, nickel, vanadium and cadmium did not meet the criteria for significance. Metal mixture analyses did not identify statistically significant associations with adolescent eGFR. Conclusions: These findings have important implications for future studies investigating the potential mechanisms through which prenatal metal exposures affect long-term kidney health in children. [ABSTRACT FROM AUTHOR]

To explore the combustion characteristics of ammonia‒hydrogen‒air flame, explosion venting experiments of ammonia‒hydrogen‒air mixtures with different equivalence ratios (ϕ), in the range of 0.6–1.7, are carried out in a 2 m long duct. The results show that the pressure‒time histories inside the duct have a three-peak structure (P b , P out , and P ext), which is caused by the burst of the vent cover, venting of burned mixtures, and counterflow flame generated by the external explosion, respectively. P out evolves into three pressure peak types with increasing ϕ. The pressure peak value P e is generated at the pressure measuring point outside the duct because of the external explosion. The change in P e with ϕ is consistent with P out and P ext , all of which increase first and then decrease with increasing ϕ and reach a maximum value at ϕ = 1.3. This study provides basic theoretical support for the promotion and application of ammonia mixed fuel. • The effects of the equivalence ratio, ϕ , on duct-vented ammonia‒hydrogen‒air deflagration were studied. • Counterflow flame generated by the external explosion was observed in all experiments. • The pressure‒time histories inside the duct under each operating condition present had a three-peak structure. • The maximum overpressure inside and outside duct first increased and thereafter decreased. [ABSTRACT FROM AUTHOR]

Polaron, a typical quasi-particle that describes a single impurity dressed with surrounding environment, serves as an ideal platform for bridging few- and many-body physics. In particular, different few-body correlations can compete with each other and lead to many intriguing phenomena. In this work, we review the recent progresses made in understanding few-body correlation effects in attractive Fermi polarons of ultracold gases. By adopting a unified variational ansatz that incorporates different few-body correlations in a single framework, we will discuss their competing effects in Fermi polarons when the impurity and majority fermions have the same or different masses. For the equal-mass case, we review the nature of polaron-molecule transition that is driven by two-body correlations, and especially highlight the finite momentum character and huge degeneracy of molecule states. For the mass-imbalanced case, we focus on the smooth crossover between polaron and various dressed clusters that originate from high-order correlations. These competing few-body correlations reviewed in Fermi polarons suggest a variety of exotic new phases in the corresponding many-body system of Fermi-Fermi mixtures. [ABSTRACT FROM AUTHOR]

Flow NMR is an expanding analytical approach with applications that include in‐line analysis for process control and optimisation, and real‐time reaction monitoring. The samples monitored by flow NMR are typically mixtures that yield complex 1D 1H spectra. “Pure shift” NMR is a powerful approach to simplifying 1H NMR spectra, but its standard implementation is not compatible with continuous flow because of interference between sample motion and the position‐dependent spin manipulations that are required in pure shift NMR. Here we show that pure shift NMR spectra can be successfully collected for continuously flowing samples, thanks to an adapted acquisition scheme, robust solvent suppression, and a velocity‐compensation strategy. The resulting method is used to collect ultrahigh resolution reaction monitoring data. Pure shift NMR spectra are expected to benefit many applications of flow NMR. [ABSTRACT FROM AUTHOR]