The Effect of Anterior Tooth Position on Trumpet Performance Quality

poster abstractObjective: Music teachers contend that the arrangement of anterior teeth affects trumpet performance by influencing the embouchure. Since there is little quantitative data to support this claim, the purpose of this study was to determine whether trumpet performance skills are associated with the malalignment of anterior teeth. Methods: Following IRB approval, 70 trumpet students (55M:15F; aged 20-38.9 yrs.) from 11 universities were consented to complete a survey concerning dental history and trumpet playing habits. The students were asked to play a scripted performance skill test (flexibility, range, endurance, and articulation exercises) on their instrument in a soundproof music practice room while being audio and video recorded. A threedimensional (3D) cone beam computerized tomograph (CBCT) was taken of each student the same day as the skill test. Following reliability studies, overjet, overbite, and degree of anterior tooth irregularity (Little’s Index) were measured on the 3D CBCT. Nonparametric correlations, accepting p0.8). Significant (p<0.05), but weak (r<0.30) associations were found only between Little’s Index of the mandibular anterior dentition and the performance skills: flexibility (exercises a, c and avg) and articulation (double tongue). No other associations were significant. Conclusions: University trumpet students with mandibular anterior teeth that are smoothly aligned have significantly better performance skills than those with misaligned mandibular anterior teeth; however, the association is weak

Sodium Glucose Cotransporter-2 (SGLT-2) Inhibitor Related Diabetic Ketoacidosis

Diabetic ketoacidosis is a rare but serious and life-threatening acute complication of diabetes mellitus. It is characterized by ketoacidosis with other findings and should be treated immediately. In this case, a 33-year-old diabetic patient who admitted to the emergency department with diabetic ketoacidosis is presented. The patient was prescribed empagliflozin (sodium glucose cotransporter inhibitor-2) a month ago. The SGLT-2 inhibitors have been approved for use in the treatment of type 2 DM and are still not used in the treatment of type 1 DM. There are such reports of unusual side effects related SGLT-2 inhibitors, in the literature and among them, ketoacidosis is a rare and important side effect

The association of malocclusion and trumpet performance

Objective:  To determine whether trumpet performance skills are associated with malocclusion. Materials and Methods:  Following institutional review board approval, 70 university trumpet students (54 male, 16 female; aged 20–38.9 years) were consented. After completing a survey, the students were evaluated while playing a scripted performance skills test (flexibility, articulation, range, and endurance exercises) on their instrument in a soundproof music practice room. One investigator (trumpet teacher) used a computerized metronome and a decibel meter during evaluation. A three-dimensional (3D) cone-beam computerized tomography scan (CBCT) was taken of each student the same day as the skills test. Following reliability studies, multiple dental parameters were measured on the 3D CBCT. Nonparametric correlations (Spearman), accepting P < .05 as significant, were used to determine if there were significant associations between dental parameters and the performance skills. Results:  Intrarater reliability was excellent (intraclass correlations; all r values > .94). Although associations were weak to moderate, significant negative associations (r ≤ −.32) were found between Little's irregularity index, interincisal inclination, maxillary central incisor rotation, and various flexibility and articulation performance skills, whereas significant positive associations (r ≤ .49) were found between arch widths and various skills. Conclusions:  Specific malocclusions are associated with trumpet performance of experienced young musicians

Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Learning feature interaction is the critical backbone to building recommender systems. In web-scale applications, learning feature interaction is extremely challenging due to the sparse and large input feature space; meanwhile, manually crafting effective feature interactions is infeasible because of the exponential solution space. We propose to leverage a Transformer-based architecture with attention layers to automatically capture feature interactions. Transformer architectures have witnessed great success in many domains, such as natural language processing and computer vision. However, there has not been much adoption of Transformer architecture for feature interaction modeling in industry. We aim at closing the gap. We identify two key challenges for applying the vanilla Transformer architecture to web-scale recommender systems: (1) Transformer architecture fails to capture the heterogeneous feature interactions in the self-attention layer; (2) The serving latency of Transformer architecture might be too high to be deployed in web-scale recommender systems. We first propose a heterogeneous self-attention layer, which is a simple yet effective modification to the self-attention layer in Transformer, to take into account the heterogeneity of feature interactions. We then introduce \textsc{Hiformer} (\textbf{H}eterogeneous \textbf{I}nteraction Trans\textbf{former}) to further improve the model expressiveness. With low-rank approximation and model pruning, \hiformer enjoys fast inference for online deployment. Extensive offline experiment results corroborates the effectiveness and efficiency of the \textsc{Hiformer} model. We have successfully deployed the \textsc{Hiformer} model to a real world large scale App ranking model at Google Play, with significant improvement in key engagement metrics (up to +2.66\%)

Nonequilibrium coupled Brownian phase oscillators

A model of globally coupled phase oscillators under equilibrium (driven by Gaussian white noise) and nonequilibrium (driven by symmetric dichotomic fluctuations) is studied. For the equilibrium system, the mean-field state equation takes a simple form and the stability of its solution is examined in the full space of order parameters. For the nonequilbrium system, various asymptotic regimes are obtained in a closed analytical form. In a general case, the corresponding master equations are solved numerically. Moreover, the Monte-Carlo simulations of the coupled set of Langevin equations of motion is performed. The phase diagram of the nonequilibrium system is presented. For the long time limit, we have found four regimes. Three of them can be obtained from the mean-field theory. One of them, the oscillating regime, cannot be predicted by the mean-field method and has been detected in the Monte-Carlo numerical experiments.Comment: 9 pages 8 figure

Irreversible and reversible modes of operation of deterministic ratchets

We discuss a problem of optimization of the energetic efficiency of a simple rocked ratchet. We concentrate on a low-temperature case in which the particle's motion in a ratchet potential is deterministic. We show that the energetic efficiency of a ratchet working adiabatically is bounded from above by a value depending on the form of ratchet potential. The ratchets with strongly asymmetric potentials can achieve ideal efficiency of unity without approaching reversibility. On the other hand we show that for any form of the ratchet potential a set of time-protocols of the outer force exist under which the operation is reversible and the ideal value of efficiency is also achieved. The mode of operation of the ratchet is still quasistatic but not adiabatic. The high values of efficiency can be preserved even under elevated temperatures

Using the stated preference method for the calculation of social discount rate

The aim of this paper is to build the stated preference method into the social discount rate methodology. The first part of the paper presents the results of a survey about stated time preferences through pair-choice decision situations for various topics and time horizons. It is assumed that stated time preferences differ from calculated time preferences and that the extent of stated rates depends on the time period, and on how much respondents are financially and emotionally involved in the transactions. A significant question remains: how can the gap between the calculation and the results of surveys be resolved, and how can the real time preferences of individuals be interpreted using a social time preference rate. The second part of the paper estimates the social time preference rate for Hungary using the results of the survey, while paying special attention to the pure time preference component. The results suggest that the current method of calculation of the pure time preference rate does not reflect the real attitudes of individuals towards future generations

Recommender Systems with Generative Retrieval

Modern recommender systems perform large-scale retrieval by first embedding queries and item candidates in the same unified space, followed by approximate nearest neighbor search to select top candidates given a query embedding. In this paper, we propose a novel generative retrieval approach, where the retrieval model autoregressively decodes the identifiers of the target candidates. To that end, we create semantically meaningful tuple of codewords to serve as a Semantic ID for each item. Given Semantic IDs for items in a user session, a Transformer-based sequence-to-sequence model is trained to predict the Semantic ID of the next item that the user will interact with. To the best of our knowledge, this is the first Semantic ID-based generative model for recommendation tasks. We show that recommender systems trained with the proposed paradigm significantly outperform the current SOTA models on various datasets. In addition, we show that incorporating Semantic IDs into the sequence-to-sequence model enhances its ability to generalize, as evidenced by the improved retrieval performance observed for items with no prior interaction history.Comment: Preprint versio

The role of fused thiophene and naphthalene diimide (NDI) in shaping the optical and electrical properties of donor-acceptor polymers

Three polymers with general structure (D-A)n were designed and synthetized to investigate the interaction of strong donors and strong acceptors in polymer chain. They are based on different fused thiophenes (1Th: 4,4′-bis(2-ethylhexyl)-cyclopenta [2,1-b:3,4- ’]dithiophene; 2Th: 4,8-bis [(2-ethylhexyl)oxy]benzo [1,2-b:4,5-b']dithiophene; 3Th: 4,8-bis(4-fluoro-5-(2-ethylhexyl)-thiophen-2-yl)benzo [1,2-b:4,5-b']bisthiophene) and N,N′-bis(2-thylhexyl)-1,8:4,5-naphthalenetetracarboxdiimide (NDI). Fused benzo- and cyclopenta-thiophene derivatives were selected because they are known for their strong electron-donating properties. NDI was coupled with them in polymer chain because it is one of the best known electron withdrawing units. Such combination of donor and acceptor units is one of the strategies for obtaining low band gap conjugated polymers with semiconducting properties for many applications. The interaction of donors and acceptors is a key factor determining the properties of such polymers. The electrochemical and spectroscopic measurement were supported by DFT calculations. Moreover, organic field effect transistors (OFET) were fabricated to demonstrate the feasibility of using the newly developed materials in electronic devices