by Subgroup. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

by Subgroup. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

Flow diagram for the 5D model. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

by Subgroup. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

Elasticities of equilibrium proportion in X. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

by age and subgroup. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

Derivatives of equilibrium proportion in X. by David McMillon (546087)

“…Finally, we discuss the implications of the model for a broader policy debate on crime control and for competing explanations of the Black-White gap in criminal involvement. We find, among other conclusions, that marginal independent increases in first-time arrest rates (but not arrest rates for repeat offenders) increase long-run crime for all subgroups; that long-run crime levels for Black men are most sensitive to initial flows into crime and arrest and to rehabilitation; and that among people with no arrest history, Black women are significantly more likely than other subgroups to desist the following year.…”

NbUCH15 promotes RipE1 stability by deubiquitination. by Wenjia Yu (9422059)

A proposed model on the impact of DHA and ARA supplementation on <i>L. vannamei</i> health. by Virak Visudtiphole (11574169)

CONSORT diagram. by Aina Gabarrell-Pascuet (17696594)

“…Statistically significant (<i>p</i><0.01) decreases in emotional loneliness and depressive symptoms were observed following the intervention. …”

S1 Dataset - by Riham Saud Alhazmy (19697677)

“…</p><p>Results</p><p>The mean HbA1c level decreased from 8.61 ± 1.70 to 7.92 ± 1.60 after implementing the WhatsApp group instructions; the values showed a significant difference (t-value = 5.107 and <i>P</i>-value < 0.001). …”

Particepant recruitment flowchart. by Riham Saud Alhazmy (19697677)

“…</p><p>Results</p><p>The mean HbA1c level decreased from 8.61 ± 1.70 to 7.92 ± 1.60 after implementing the WhatsApp group instructions; the values showed a significant difference (t-value = 5.107 and <i>P</i>-value < 0.001). …”

Flow of participants through the study. by Sedighe Esmaeilzadeh (21100668)

“…Furthermore, melatonin significantly decreased sleep latency, exhibiting a large effect size, and contributed to a medium reduction in the use of sleep medications. …”

Demographic Characteristics of Participants. by Sedighe Esmaeilzadeh (21100668)

“…Furthermore, melatonin significantly decreased sleep latency, exhibiting a large effect size, and contributed to a medium reduction in the use of sleep medications. …”

Results of longitudinal analysis of mental health in HCWs. by A. H. Ayesha Lavell (16734002)

Baseline characteristics. by Daniela Sánchez-Santiesteban (21192342)

“…</p><p>Results</p><p>The cohort included 1,913 formal employees (mean age: 49.9 years), with 660 deaths (34.5%) recorded over the follow-up period. …”

Summary of subscales or questions utilized to define traits. by Dai Nogimura (21445649)

Demographic and ocular features. by Mingxi Shao (10066570)

“…Pearson analysis revealed significant negative correlations: SOD with anterior chamber depth (r = −0.445, p = 0.012) and H₂O₂ with mean deviation values for the visual field (r = −0.412, p = 0.041). …”

Machine learning model to diagnose PCG. by Mingxi Shao (10066570)

“…Pearson analysis revealed significant negative correlations: SOD with anterior chamber depth (r = −0.445, p = 0.012) and H₂O₂ with mean deviation values for the visual field (r = −0.412, p = 0.041). …”

ROC curves of TAS + SOD + MDA to diagnose PCG. by Mingxi Shao (10066570)

“…Pearson analysis revealed significant negative correlations: SOD with anterior chamber depth (r = −0.445, p = 0.012) and H₂O₂ with mean deviation values for the visual field (r = −0.412, p = 0.041). …”