Short-distance constraints for HLbL in muon g-2

Model-independent short-distance constraints allow for a reduction of theoretical uncertainties associated to the analytic evaluation of Hadronic Light-by-Light contributions to the muon g-2. In this talk we focus on the region where the three loop virtualities are large. Even when the fourth photon leg is soft, we show how a precise Operator Product Expansion can be applied in that region. The leading contribution is found to be given by the quark loop, while the evaluation of both gluonic and power corrections show how the expansion is well behaved at relatively low energies, where significant contributions to the muon g-2 remain. Numerical values for them are also presented.

Evaluation of computational models of infant language development against robust empirical data from meta-analyses: what, why, and how?

Computational models of child language development can help us understand the cognitive underpinnings of the language learning process. One advantage of computational modeling is that is has the potential to address multiple aspects of language learning within a single learning architecture. If successful, such integrated models would help to pave the way for a more comprehensive and mechanistic understanding of language development. However, in order to develop more accurate, holistic, and hence impactful models of infant language learning, the research on models also requires model evaluation practices that allow comparison of model behavior to empirical data from infants across a range of language capabilities. Moreover, there is a need for practices that can compare developmental trajectories of infants to those of models as a function of language experience. The present study aims to take the first steps to address these needs. More specifically, we will introduce the concept of comparing models with large-scale cumulative empirical data from infants, as quantified by meta-analyses conducted across a large number of individual behavioral studies. We start by formalizing the connection between measurable model and human behavior, and then present a basic conceptual framework for meta-analytic evaluation of computational models together with basic guidelines intended as a starting point for later work in this direction. We exemplify the meta-analytic model evaluation approach with two modeling experiments on infant-directed speech preference and native/non-native vowel discrimination. We also discuss the advantages, challenges, and potential future directions of meta-analytic evaluation practices.

A SUSTAINABILITY OPTION: A META-ANALYTIC EVALUATION OF RAIL SERVICE QUALITY IN PUBLIC TRANSPORTATION STUDY AND PASSENGER SATISFACTION

These contradictory findings, as well as the increased emphasis among transport professionals on having satisfied passengers, highlight the important information on passenger pleasure to appraise existing data. And also evaluate the meta-analytical relationship of the reported passenger satisfaction findings. However, the equity and disconfirmation model are most significantly associated with passenger satisfaction, according to the document. Discovery shows that the analysis measures and procedure elements often alter the strength of the association between satisfaction and its experiences and outcomes. The authors examined the consequences of these impacts and suggest numerous research avenues for future study.

EVALUASI ANALITIK POCT METODE GLUCOSE DEHYDROGENASE PARAMETER GLUKOSA PADA SPESEIMEN SERUM DAN PLASMA EDTA

Diabetes is a non-communicable disease that can be prevented and detected as early as possible by routine glucose checks. Point Of Care Testing (POCT) as a diabetes test screening tool is widely used by health care institutions and is even used independently by the wider community. Blood glucose can be measured by serum, plasma, and whole blood specimens. The standard specimen for glucose measurement using POCT is whole blood. Based on the author's survey, the use of the POCT tool in several health care institutions was not following the insert of the tool kit, one of which was the type of specimen used. Many laboratories use EDTA serum and plasma specimens for glucose testing using the POCT device. There are many methods used in the POCT tool, one of these methods is the glucose dehydrogenase method. Therefore analytic evaluation is necessary to ensure the accuracy and accuracy of laboratory examination results in glucose examination. This type of research is the analytical method with a comparative design. The data was collected using the total sampling method. The data is reported using Microsoft Excel and SPSS applications. The number of samples for analytic evaluation was 40 samples. Based on the results of tests performed in duplicate, there were clinical differences in glucose values using serum and plasma EDTA samples so that the use of these samples was not suitable for use for diagnostic purposes using the POCT glucose dehydrogenase method. There was a statistical difference in serum glucose and plasma EDTA against whole blood that was examined using the POCT glucose dehydrogenase method with a correlation value (R) of 0.9722 and 0.9695.

A Meta-Analytic Evaluation of Naglieri Nonverbal Ability Test: Exploring Its Validity Evidence and Effectiveness in Equitably Identifying Gifted Students

The Naglieri Nonverbal Ability Test (NNAT) was developed to more equitably identify students of color, as it advertises itself as a culture-fair measure. In this meta-analytic evaluation, we aimed to investigate (a) the generalizability of validity evidence of NNAT by checking its construct and criterion validity with other measures (Part I) and (b) whether NNAT truly meets its goal to identify more culturally diverse students (Part II). After reviewing 1,714 studies, a total of 29 studies met our criteria (59 effect sizes from 22 studies for Part I and 7 effect sizes from 7 studies for Part II). In Part I, we investigated empirical evidence of validity of NNAT in relationship with different types of measures (overall effect size of r was .44); The results revealed that the correlation between NNAT and the achievement test results was 0.68, followed by the intelligence measures similar to NNAT (e.g., Cognitive Abilities Test, Otis–Lennon School Ability Tests; r = .31) and other alternative measures often used to identify gifted students (e.g., teacher-rating scale; r = .20). The moderator analysis results showed high correlations between NNAT and other measures when Naglieri is an author of the study. In Part II, although NNAT identified more students of color compared with other nonverbal tests (overall effect size of risk ratio was 0.42), findings revealed that students of color remain underrepresented in gifted programs and services.