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The growth mindset or the belief that intelligence is malleable has garnered significant attention for its positive association with academic success. Several recent randomized trials, including the National Study of Learning Mindsets (NSLM), have been conducted to understand why, for whom, and under what contexts a growth mindset intervention can promote beneficial achievement outcomes during critical educational transitions. Prior research suggests that the NSLM intervention was particularly effective in improving low-achieving 9th graders’ GPA, while the impact varied across schools. In this study, we investigated the underlying causal mediation mechanism that might explain this impact and how the mechanism varied across different types of schools. By extending a recently developed weighting method for multisite causal mediation analysis, the analysis enhances the external and internal validity of the results. We found that challenge-seeking behavior played a significant mediating role, only in medium-achieving schools, which may partly explain the reason why the intervention worked differently across schools. We conclude by discussing implications for designing interventions that not only promote students’ growth mindsets but also foster supportive learning environments under different school contexts. 

Local outlier techniques are known to be effective for detecting outliers in skewed data, where subsets of the data exhibit diverse distribution properties. However, existing methods are not well equipped to support modern high-velocity data streams due to the high complexity of the detection algorithms and their volatility to data updates. To tackle these shortcomings, we propose local outlier semantics that operate at an abstraction level by leveraging kernel density estimation (KDE) to effectively detect local outliers from streaming data. A strategy to continuously detect top-N KDE-based local outliers over streams is designed, called KELOS – the first linear time complexity streaming local outlier detection approach. The first innovation of KELOS is the abstract kernel center-based KDE (aKDE) strategy. aKDE accurately yet efficiently estimates the data density at each point – essential for local outlier detection. This is based on the observation that a cluster of points close to each other tend to have a similar influence on a target point’s density estimation when used as kernel centers. These points thus can be represented by one abstract kernel center. Next, the KELOS’s inlier pruning strategy early prunes points that have no chance to become top-N outliers. This empowers KELOS to skip the computation of their data density and of the outlier status for every data point. Together aKDE and the inlier pruning strategy eliminate the performance bottleneck of streaming local outlier detection. The experimental evaluation demonstrates that KELOS is up to 6 orders of magnitude faster than existing solutions, while being highly effective in detecting local outliers from streaming data. 

This study provides a template for multisite causal mediation analysis using a comprehensive weighting-based analytic procedure that enhances external and internal validity. The template incorporates a sample weight to adjust for complex sample and survey designs, adopts an IPTW weight to adjust for differential treatment assignment probabilities, employs an estimated nonresponse weight to account for non-random nonresponse, and utilizes a propensity score-based weighting strategy to flexibly decompose not only the population average but also the between-site heterogeneity of the total program impact. Because the identification assumptions are not always warranted, a weighting-based balance checking procedure assesses the remaining overt bias, while a weighting-based sensitivity analysis further evaluates the potential bias related to omitted confounding or to propensity score model misspecification. We derive the asymptotic variance of the estimators for the causal effects that account for the sampling uncertainty in the estimated weights. The method is applied to a re-analysis of the data from the National Job Corps Study. 

A<sc>bstract</sc> Inclusive and differential cross sections for Higgs boson production in proton-proton collisions at a centre-of-mass energy of 13.6 TeV are measured using data collected with the CMS detector at the LHC in 2022, corresponding to an integrated luminosity of 34.7 fb⁻¹. Events with the diphoton final state are selected, and the measured inclusive fiducial cross section is$${\sigma }_{\text{fid}}={74}\pm {11}{\left({\text{stat}}\right)}_{-4}^{+5}\left({\text{syst}}\right)$$fb, in agreement with the standard model prediction of 67.8 ± 3.8 fb. Differential cross sections are measured as functions of several observables: the Higgs boson transverse momentum and rapidity, the number of associated jets, and the transverse momentum of the leading jet in the event. Within the uncertainties, the differential cross sections agree with the standard model predictions. 

Incoherent $J/\psi$photoproduction in heavy ion ultraperipheral collisions (UPCs) provides a sensitive probe of localized, fluctuating gluonic structures within heavy nuclei. This Letter reports the first measurement of the photon-nucleon center-of-mass energy ( $W_{\gamma \mathrm{N}}$) dependence of this process in PbPb UPCs at a nucleon-nucleon center-of-mass energy of 5.02 TeV, using $1.52{\mathrm{nb}}^{-1}$of data recorded by the CMS experiment. The measurement covers a wide $W_{\gamma \mathrm{N}}$range of $\approx 40–400\mathrm{GeV}$, probing gluons carrying a fraction $x$of nucleon momentum down to an unexplored regime of $6.5\times {10}^{-5}$. Compared to baseline predictions neglecting nuclear effects, the measured cross sections exhibit significantly greater suppression at lower $x$. Additionally, the ratio of incoherent to coherent photoproduction is found to be constant across the probed $W_{\gamma \mathrm{N}}$and $x$range, disfavoring the establishment of the black disk limit. This Letter provides critical insights into the $x$-dependent evolution of fluctuating gluonic structures within nuclei and calls for further advancements in theoretical models incorporating nuclear shadowing and gluon saturation. 

A<sc>bstract</sc> A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at$$\sqrt{s}=13$$TeV, corresponding to an integrated luminosity of 138 fb⁻¹. In this search, a flavor-changing neutral current produces a single top quark or antiquark and an invisible state nonresonantly. The invisible state consists of a hypothetical spin-1 particle acting as a new mediator and decaying to two spin-1/2 dark matter candidates. The analysis searches for events in which the top quark or antiquark decays hadronically. No significant excess of events compatible with that signature is observed. Exclusion limits at 95% confidence level are placed on the masses of the spin-1 mediator and the dark matter candidates, and are compared to constraints from the dark matter relic density measurements. In a vector (axial-vector) coupling scenario, masses of the spin-1 mediator are excluded up to 1.85 (1.85) TeV with an expectation of 2.0 (2.0) TeV, whereas masses of the dark matter candidates are excluded up to 0.75 (0.55) TeV with an expectation of 0.85 (0.65) TeV.