Mobile-based trading apps have made investing easier than ever before, but this includes enabling access to risky investments that many investors may not be able to trade safely. The UK financial regulator thereby requires Contract for Difference (CFD) trading apps to make disclosures such as, ‘89% of retail investor accounts lose money when trading CFDs with this provider’. However, these disclosures might be counteracted by either their suboptimal implementation, or by other aspects of these apps’ deceptive choice architecture. Therefore, the present study audited choice architecture characteristics of demo-modes of the 14 most-popular CFD trading apps in the UK. A content analysis found for example that 31.6% of risk warnings did not comply with the regulator’s standards, and that only 35.7%% of apps contained risk warnings within the app’s main tabs. A thematic analysis suggested that apps’ educational resources could instil users with the hope of winning, by emphasising practice, strategies and psychological mindset – instead of acknowledging luck as the predominant factor underlying CFD trading profitability. Overall, this study added to previous research highlighting the similarities between certain high-risk investments and gambling, and added to the behavioural public policy literature on deceptive choice architecture.

We report on Lagrangian statistics of turbulent Rayleigh–Bénard convection under very different conditions. For this, we conducted particle tracking experiments in a $H=1.1$-m-high cylinder of aspect ratio $\varGamma =1$ filled with air (Pr = 0.7), as well as in two rectangular cells of heights $H=0.02$ m ($\varGamma =16$) and $H=0.04$ m ($\varGamma =8$) filled with water (Pr = 7.0), covering Rayleigh numbers in the range $10^6\le {\textit {Ra}}\le 1.6\times 10^9$. Using the Shake-The-Box algorithm, we have tracked up to 500 000 neutrally buoyant particles over several hundred free-fall times for each set of control parameters. We find the Reynolds number to scale at small Ra (large Pr) as $ {\textit{Re}} \propto {\textit{Ra}}^{0.6}$. Further, the averaged horizontal particle displacement is found to be universal and exhibits a ballistic regime at small times and a diffusive regime at larger times, for sufficiently large $\varGamma$. The diffusive regime occurs for time lags larger than $\tau _{co}$, which is the time scale related to the decay of the velocity autocorrelation. Compensated as $\tau _{co} {\textit {Pr}}^{-0.3}$, this time scale is universal and rather independent of $ {\textit {Ra}}$ and $\varGamma$. We have also investigated the Lagrangian velocity structure function $S^2_i(\tau )$, which is dominated by viscous effects for times smaller than the Kolmogorov time $\tau _\eta$ and hence $S^2_i\propto \tau ^2$. For larger times we find a novel scaling for the different components with exponents smaller than what is expected in the inertial range of homogeneous isotropic turbulence without buoyancy. Studying particle-pair dispersion, we find a Batchelor scaling (${\propto }\,t^2$) on small time scales, diffusive scaling (${\propto }\,t$) on large time scales and Richardson-like scaling (${\propto }\,t^3$) for intermediate time scales.

X-ray diffraction (XRD) characterization of natural and intercalated smectites is usually limited to the apparent d-value estimated from the peak maxima in the raw data. This can lead to the misinterpretation of the measured data. In the case of XRD, the interference function is modulated by instrumental factors (Lorentz-polarization factor, diffraction geometry) and physical factors (structure factor, surface roughness effect). These effects lead to diffraction profile distortions, depending on the diffraction angle and peak full width at half maximum (FWHM). As a result, the diffraction profiles for structures with large line broadening (FWHM > 1°) exhibit a significant peak shift (Δd ∼ 1.5 Å), especially at low angles (2θ ≤ 10°). The present work deals with the detailed analysis of all these effects, their corrections and their consequences for the interpretation of diffraction patterns (including possible errors in determining lattice parameters or the structure model). The investigated materials were montmorillonites (MMT) intercalated with hydroxy-Al polymers. Diffraction profile analysis revealed the corrected d-values and showed that the intercalated sample is not a mixed-layered structure. As a result a structural model of the interlayer is presented.

Languages vary in the mapping of relational terms onto events. For instance, English motion descriptions favor manner (how something moves) verbs over path (where something move) verbs, whereas those of other languages, like Spanish, show the opposite pattern. While these lexicalization biases are malleable, adopting a novel lexicalization pattern can be slow for second language learners. One potential mechanism for learning non-native verb mappings is cross-situational statistical learning (CSSL). However, the application of CSSL to verbs is limited and does not explicitly examine how lexicalization biases may complicate adults’ ability to resolve the referential uncertainty of multiple referents. We ask English-speaking monolingual adults to learn the mappings of ten verbs via CSSL. Verbs mapped onto either manner or path of motion, with the other event component held constant. Adults in both conditions demonstrated successful learning of novel verbs, with adults learning the manner verbs showing more consistent performance across accepting correct referents and rejecting incorrect ones. Our results are the first to demonstrate adults’ use of CSSL to acquire verb meanings that both align with and cut against native lexicalization biases and suggest a limited influence of lexicalization biases on adults’ learning in idealized CSSL conditions.

We evaluated a digital learning programme for non-specialists to develop knowledge-based competencies in a problem-solving intervention for adolescents to examine the overall impact of training on knowledge-based competencies among learners; and to compare the effects of two training conditions (self-guided digital training with or without coaching) in a nested parallel, two-arm, individually randomised controlled trial. Eligible participants were 18 or older; fluent in Hindi or English; able to access digital training; and had no prior experience of delivering structured psychotherapies. 277 participants were enrolled from 31 March 2022 to 19 June 2022 of which 230 (83%) completed the study. There was a significant increase in competency score from pre-training (Mean = 7.01, SD = 3.29) to post-training (Mean = 8.88, SD = 3.80), 6 weeks after the pre-training assessment. Knowledge competency scores showed larger increase among participants randomised to the coaching arm (AMD = 1.09, 95% CI 0.26–1.92, p = 0.01) with an effect size (d) of 0.33 (95% CI 0.08–0.58). More participants completed training in the coaching arm (n = 96, 69.6%) compared to the self-guided training arm (n = 56, 40.3%). In conclusion, a coach-supported remote digital training intervention is associated with enhanced participation by learners and increased psychotherapeutic knowledge competencies.