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The multi variate mixture dynamics model is a tractable, dynamical, arbitrage-free multivariate model characterized by transparency on the dependence structure, since closed form formulae for terminal correlations, average correlations and copula function are available. It also allows for complete decorrelation between assets and instantaneous variances. Each single asset is modelled according to a lognormal mixture dynamics model, and this univariate version is widely used in the industry due to its flexibility and accuracy. The same property holds for the multivariate process of all assets, whose density is a mixture of multivariate basic densities. This allows for consistency of single asset and index/portfolio smile. In this paper, we generalize the MVMD model by introducing shifted dynamics and we propose a definition of implied correlation under this model. We investigate whether the model is able to consistently reproduce the implied volatility of FX cross rates once the single components are calibrated to univariate shifted lognormal mixture dynamics models. We consider in particular the case of the Chinese Renminbi FX rate, showing that the shifted MVMD model correctly recovers the CNY/EUR smile given the EUR/USD smile and the USD/CNY smile, thus highlighting that the model can also work as an arbitrage free volatility smile extrapolation tool for cross currencies that may not be liquid or fully observable. We compare the performance of the shifted MVMD model in terms of implied correlation with those of the shifted simply correlated mixture dynamics model where the dynamics of the single assets are connected naively by introducing correlation among their Brownian motions. Finally, we introduce a model with uncertain volatilities and correlation. The Markovian projection of this model is a generalization of the shifted MVMD model.

Purpose The purpose of this study was to investigate the aesthetics evaluation of four smile-related characteristics among different genders and professional subgroups, including dental professionals (DPs), non-dental healthcare professionals (NDPs), and laypersons (LPs). Methods Smile photographs were selected and digitally manipulated to determine changes in various smile aesthetic parameters (lip thickness ratio, smile line/smile index, upper lip curvature, and smile arc/dental curvature). These altered images were rated by Chinese participants (dental professionals, non-dental healthcare professionals, and laypersons). A total of 1469 subjects were recruited to complete the questionnaire. Smile aesthetics ratings were calculated, and comparisons between groups were made. Results All respondents chose 1:1.5 lip thickness ratio, average smile line, upward upper lip curvature, and upward dental curvature (consonant smile arc) parallel to the lower lip curvature smile arc as the most attractive. Dental professionals (DPs) more focus on smile aesthetics compared to the others( p  < 0.01). Significant differences were detected in the perception of smile-related characteristics across gender and professional subgroups( p  < 0.05). In addition, there were significant differences in the attractiveness ratings for smiles among professional subgroups( p  < 0.05). The most important factor influencing smile aesthetics in the present study was smile arc. Conclusion The smile-related characteristics of the smile, such as the lip thickness ratio, smile line, upper lip curvature, and smile arc are predominant factors influencing smile attractiveness and should be given priority when considering and managing aesthetic treatment plans. Females and DPs are more critical of smile aesthetics, and DPs are also focused more on smile aesthetics than laypersons. So it is necessary to account for the influence of gender and profession on personal evaluation and treatment plans.

Kateryna Fedchuk,1 Olga Grossenbacher,1 Antonio Leccisotti2–4 1Ziemer Ophthalmic Systems, Port, Switzerland; 2Siena Eye Laser, Poggibonsi, Siena, Italy; 3Center for Research in Refractive Surgery, Poggibonsi, Siena, Italy; 4School of Biomedical Sciences, Ulster University, Coleraine, UKCorrespondence: Kateryna Fedchuk, Ziemer Ophthalmic Systems, Port, Switzerland, Tel +41 79 958 25 62, Email Kateryna.Fedchuk@ziemergroup.com

IntroductionThe primary objective was to show our initial surgical single-site experience with small incision lenticule extraction (SMILE) after the official enrollment in March 2017 following Food and Drug Administration (FDA) approval for simple myopia in late 2016 in the United States and, subsequently, compare our results to the earliest and most advanced generation of excimer platforms for laser-assisted in situ keratomileusis (LASIK) surgery.MethodsThis was a retrospective single-site study of 68 eyes from 35 patients who had SMILE surgery. The patients’ preoperative and postoperative uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), manifest sphere, manifest cylinder, intraoperative complications, and preoperative and postoperative visual symptoms were collected. We compared our findings to the results from the FDA SMILE study, and to the three earliest (1999–2000) and three of the most updated (2013–2016) platforms for LASIK.ResultsThe cumulative UDVA was 20/20 and 20/40 or better in 74% and 100% of patients, respectively. The intended target refraction was within ± 0.5 and ± 1.00 D in 80% and 93% of cases, respectively. The prevalence of dry eyes decreased by nearly half from 1-week to the 6-month postoperative interval. Patients noted improvement in glare (17%), halos (17%), fluctuation (25%), and depth perception (8%) at the 6-month interval compared to preoperative levels.ConclusionsThis study’s findings are consistent with current SMILE reports. Notably, the results are superior to the earliest generation of LASIK, however inferior to the latest excimer platforms. SMILE does meet the efficacy and safety criteria met by FDA; however, there is a definite need for further improvement to reach the superior refractive outcomes produced by the latest generation of LASIK platforms.

Sabrina M Miller,1,* Mina M Sitto,2,3,* Kayvon A Moin,2,4 Phillip C Hoopes,2 Majid Moshirfar2,5,6 1Department of Neurology and Ophthalmology, Michigan State University College of Osteopathic Medicine, East Lansing, MI, USA; 2Hoopes Moshirfar Research Center, Hoopes Vision, Draper, UT, USA; 3Department of Ophthalmology, Wayne State University School of Medicine, Detroit, MI, USA; 4Department of Ophthalmology, Nassau University Medical Center, East Meadow, NY, USA; 5John A. Moran Eye Center, University of Utah School of Medicine, Salt Lake City, UT, USA; 6Utah Lions Eye Bank, Murray, UT, USA*These authors contributed equally to this workCorrespondence: Majid Moshirfar, Hoopes Moshirfar Research Center, 11820 S. State St. #200, Draper, UT, 84020, USA, Tel +1 801-568-0200, Fax +1 801-563-0200, Email cornea2020@me.com

Smile aesthetics is an important factor to consider during orthodontic treatment planning. The aim of the present study is to assess the predictability of Invisalign SmileView for digital AI smile simulation in comparison to actual smile treatment outcomes, using various smile assessment parameters. A total of 24 adult subjects (12 females and 12 males; mean age 22 ± 5.2 years) who chose to be treated using Invisalign were prospectively recruited to have their pretreatment smiles captured using the Invisalign SmileView to simulate their new smiles before treatment was started. Patients were then treated using upper and lower Invisalign aligners with average treatment time of 18 ± 6 months. Full post-treatment records were obtained and full smile frame images of simulated smile and actual final smile of each subject were evaluated by an independent examiner using an objective assessment sheet. Ten smile variants were used to assess the characteristics of the full smile images. Significance level was set at P < 0.05. The ICC for the quantitative parameters showed that there was an overall excellent & good internal consistency (alpha value > 0.7 & > 0.9). The Independent t test was performed amongst the quantitative variables. The P value was not significant for all except maxillary inter canine width (P = 0.05), stating that for the five variables namely; philtrum height, commissure height, smile width, buccal corridor and smile index, actual mean values were similar to the simulation mean values. For the qualitative variables, the Kappa value ranged between 0.66 and − 0.75 which showed a substantial level of agreement between the examiners. Additionally, the Chi square test for the qualitative variables, revealed that the P value was found to be significant in all except lip line. This implies that only the lip line values are comparable. More optimal lip lines, straighter smile arcs and more ideal tooth display were achieved in actual post treatment results in comparison to the initially predicted smiles. Five quantitative smile assessment parameters i.e., philtrum height, commissure height, smile width, buccal corridor, and smile index, could be used as reliable predictors of smile simulation. Maxillary inter canine width cannot be considered to be a reliable parameter for smile simulation prediction. A single qualitative parameter, namely the lip line, can be used as a reliable predictor for smile simulation. Three qualitative parameters i.e., most posterior tooth display, smile arc, and amount of lower incisor exposure cannot be considered as reliable parameters for smile prediction. Trial Registration number and date : NCT06123585, (09/11/2023)

Objectives: To determine the extent to which anteroposterior head inclination influences smile arc curvature assessment on frontal photographs. Materials and Methods: Sixty-three young adults participated in this study. Each had five standardized frontal-view photographs captured with posed smiles at five anteroposterior head inclinations (−20°, −10°, 0°, +10°, +20°) using a cervical range of motion device. Two curves were traced per photograph: one following the shape of the lower lip and the other the incisal edge of the maxillary anterior teeth from canine to canine (smile line). These curvatures were approximated by quadratic function and compared for concordance based on the maximum curvature of the obtained functions. A score was calculated, with 0 denoting a consonant smile (perfect concordance) and 2 a non-consonant smile. Results: Among the sixty-three participants, fifty-nine were included in the analysis after excluding those with insufficient tooth exposure in the photographs for the smile line assessment. The analysis revealed that the perceived smile line was more consonant (concordant with lower lip curvature) with a −20° head anteroposterior inclination (score: 0.146), and the least consonant with +20° anteroposterior inclination (score: 1.326), with statistically significant differences (p < 0.05). Conclusions: The smile arc curvature assessment on frontal photographs may be influenced by the anteroposterior inclination of the head on frontal photographs. However, due to the two-dimensional nature of this study, further investigations incorporating three-dimensional imaging are recommended.

Electrostimulation can be an interesting and effective alternative or additional option to conventional treatments for facial paralysis, helping to prevent atrophy of the facial muscles following denervation caused by various factors. The success of electrostimulation depends on correctly selecting the stimulation parameters applied. Our study aims to evaluate whether needle electrodes (mimicking implantable electrodes) can selectively activate the zygomaticus muscle (ZYG) in patients with facial paralysis. Ten patients were recruited. Two monopolar needle electrodes, placed under ultrasound guidance, were used to deliver bipolar electrostimulation to the affected ZYG. The stimulation was conducted under general anaesthesia in three patients and under local anaesthesia in four patients. Three patients underwent stimulation in both settings. Selectivity of stimulation was assessed by visually detecting movement of the respective mouth corner, in the absence of contractions or co-contractions of other facial muscles or discomfort. A selective Zygomaticus response was observed in all patients with pulse widths between 0.5 and 5 ms and amplitudes between 1.5 and 2.5 mA when awake, and between 1.5 and 9 mA when under general anaesthesia. No adverse events or unspecific responses from other facial muscles were observed. The duration of facial paralysis did not significantly affect parameter selection. In conclusion, our initial results suggest that stimulation parameters compatible with implantable devices can elicit a specific response from the target muscle. Ultrasound-guided electrode placement ensures the safety of the procedure. If implanted into the ZYG, a fully implantable electrostimulation device should be able to increase muscle tone and trigger a contraction, enabling a bionic smile.

Recurrent Neural Networks (RNNs) trained with a set of molecules represented as unique (canonical) SMILES strings, have shown the capacity to create large chemical spaces of valid and meaningful structures. Herein we perform an extensive benchmark on models trained with subsets of GDB-13 of different sizes (1 million, 10,000 and 1000), with different SMILES variants (canonical, randomized and DeepSMILES), with two different recurrent cell types (LSTM and GRU) and with different hyperparameter combinations. To guide the benchmarks new metrics were developed that define how well a model has generalized the training set. The generated chemical space is evaluated with respect to its uniformity, closedness and completeness. Results show that models that use LSTM cells trained with 1 million randomized SMILES, a non-unique molecular string representation, are able to generalize to larger chemical spaces than the other approaches and they represent more accurately the target chemical space. Specifically, a model was trained with randomized SMILES that was able to generate almost all molecules from GDB-13 with a quasi-uniform probability. Models trained with smaller samples show an even bigger improvement when trained with randomized SMILES models. Additionally, models were trained on molecules obtained from ChEMBL and illustrate again that training with randomized SMILES lead to models having a better representation of the drug-like chemical space. Namely, the model trained with randomized SMILES was able to generate at least double the amount of unique molecules with the same distribution of properties comparing to one trained with canonical SMILES.

The nature of a person’s motivation (whether it is intrinsic or extrinsic) is a key predictor of how committed they are to a task, and hence how well they are likely to perform at it. However, it is difficult to reliably communicate and make inferences about such fine nuances regarding another person’s motivation. Building on the social functional view of emotion and the evolutionary and psychophysical characteristics of facial expression of emotions, this research suggests that displayed enjoyment, as evidenced by the size and type of someone’s smile, can serve as a strong nonverbal signal of intrinsic motivation. Taking the perspective of both actors and observers, five studies show that people infer greater intrinsic motivation when they see others display large Duchenne (vs. small) smiles, and that actors intuit this relationship, strategically displaying larger and more Duchennelike smiles if they have an accessible goal to signal intrinsic (vs. extrinsic or no specific) motivation.