Turbulent Jet Expansion

This report was made to study the velocity distribution in an open, in a partially open, and in a partially expanding jet. The open-jet observations reveal minor systematic discrepancies from Tollmien's theoretical velocity distribution. The shearing-stress distribution for the partially open jet was determined. The value derived for the ratio of mixing distance to jet width was found to be in close agreement with the corresponding value for the open-jet boundary. The streamline pattern in a partially expanding channel was obtained from the observed velocity distribution and plotted, after which the distribution of the mixing distance for this case was also ascertained

Polarised Quark Distributions in the Nucleon from Semi-Inclusive Spin Asymmetries

We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.Comment: 17 page

Polarised quark distributions in the nucleon from semi-inclusive spin asymmetries

We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1~GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10~GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) {\rm d}x = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) {\rm d}x = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) {\rm d}x= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) {\rm d}x$.We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range 0.0031 GeV 2 . Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at Q 2 =10 GeV 2 . The polarised u valence quark distribution, Δu v ( x ), is positive and the polarisation increases with x . The polarised d valence quark distribution, Δd v ( x ), is negative and the non-strange sea distribution, Δ q ̄ (x) , is consistent with zero over the measured range of x . We find for the first moments ∫ 0 1 Δu v (x) d x=0.77±0.10±0.08 , ∫ 0 1 Δd v (x) d x=−0.52±0.14±0.09 and ∫ 0 1 Δ q ̄ (x) d x=0.01±0.04±0.03 , where we assumed Δ u ̄ (x)=Δ d ̄ (x) . We also determine for the first time the second moments of the valence distributions ∫ 0 1 xΔq v (x) d x

Spin asymmetries A1 and structure functions g1 of the proton and the deuteron from polarized high energy muon scattering.

Adeva B, Akdogan T, Arik E, et al. Spin asymmetries A(1) and structure functions g(1) of the proton and the deuteron from polarized high energy muon scattering. Phys.Rev. D. 1998;58(11): 112001.We present the final results of the spin asymmetries A(1) and the spin structure functions g(1) of the proton and the deuteron in the kinematic range 0.0008 < x < 0.7 and 0.2 < Q(2) < 100 GeV2. For the determination of A(1), in addition to the usual method which employs inclusive scattering events and includes a large radiative background at low x, we use a new method which minimizes the radiative background by selecting events with at least one hadron as well as a muon in the final state. We find that this hadron method gives smaller errors for x < 0.02, so it is combined with the usual method to provide the optimal set of results. [S0556-2821(98)07017-9]

Multilevel and empirical reliability estimates of learning growth: A simulation study and empirical illustration

Reliable learning progress information is crucial for teachers’ interpretation and data-based decision making in everyday classrooms. Slope estimates obtained from simple regression modeling or more complex latent growth models are typically used in this context as indicators of learning progress. Research on progress monitoring has used mainly two ways to estimate reliability of learning progress, namely (a) split-half reliability and (b) multilevel reliability. In this work we introduce empirical reliability as another attractive alternative to quantify measurement precision of slope estimates (and intercepts) in learning progress monitoring research. Specifically, we extended previous work on slope reliability in two ways: (a) We evaluated in a simulation study how well multilevel reliability and empirical reliability work as estimates of slope reliability, and (b) we wanted to better understand reliability of slopes as a latent variable (by means of empirical reliability) vs. slopes as an observed variable (by means of multilevel reliability). Our simulation study demonstrates that reliability estimation works well over a variety of different simulation conditions, while at the same time conditions were identified in which reliability estimation was biased (i.e., with very poor data quality, eight measurement points, and when empirical reliability was estimated). Furthermore, we employ multilevel reliability and empirical reliability to estimate reliability of intercepts (i.e., initial level) and slopes for the quop-L2 test. Multilevel and empirical reliability estimates were comparable in size with only slight advantages for latent variable scores. Future avenues for research and practice are discussed

Automating Creativity Assessment in Engineering Design: A Psychometric Validation of AI-Generated Design Problems

Creativity is essential for engineering design, yet its assessment remains challenging due to the resource-intensive nature of traditional evaluation methods. This study investigates the potential of automatic item generation (AIG) using large language models (LLMs) to create psychometrically sound assessment items for measuring creative thinking in engineering. We developed and validated engineering design problems across three domains: ability difference and limitations (e.g., assisting people with learning impairments), transportation and mobility (e.g., reducing traffic congestion in mega cities), and social environments and systems (e.g., improving access to clean water in remote areas). The study comprised three phases with samples matched on race and ethnicity: (1) content validation with a diverse sample of 40 engineers evaluating item clarity and validity, (2) item administration to 462 engineering students, and (3) response evaluation by 65 expert raters assessing originality and effectiveness. Results demonstrated that LLM-generated items achieved comparable or higher content validity rates compared to expert-written items (43% vs. 20% success rate). Bayesian confirmatory factor analysis supported a unidimensional model for fluency, originality, and effectiveness scores, with excellent reliability estimates (ranging from .92 to .95). While fluency showed minimal correlation with originality (r = -.11) and effectiveness (r = -.04), originality and effectiveness demonstrated a strong positive correlation (r = .73). The present research advances our understanding of automated assessment generation in engineering education, provides empirical evidence for the psychometric properties of AI-generated creativity tasks, and offers a scalable approach for measuring creative thinking in engineering classrooms