Drug abuse
Problem of Co-Occurring Disorders Among Jail Detainees
Pretrial Drug Testing and Defendant Risk
Heroin Use Among Southern Arrestees: Regional Findings From the Arrestee Drug Abuse Monitoring Program
Prescription Drug Misuse in Late Adulthood: An Empirical Examination of Competing Explanations
Associations of Couples Intimate Partner Violence in Young Adulthood and Substance Use: A Dyadic Approach
Identifying a Drug Use Typology of Philadelphia Arrestees: A Cluster Analysis
Crack Abusers and Noncrack Abusers: Profiles of Drug Use, Drug Sales and Nondrug Criminality
Role of Drug and Alcohol Abuse in Domestic Violence and Its Treatment: Dade County's Domestic Violence Court Experiment; Final Report
Process Evaluation of the Multnomah County Drug Testing and Evaluation Program
Substance Abuse, Employment, and Welfare Tenure
The Application of Gold Nanoparticles for the Trace Detection of Synthetic Cannabinoids in Saliva and Urine by Surface Enhanced Raman Spectroscopy
TECHBeat, March 2018
TECHBeat, October 2017
Optimization of Pretreatment Parameters in Hair Analysis for Drugs of Abuse and Understanding Protein-Drug Physicochemical Interactions
Through the Looking Glass Part II: Abuse of the Evolving Electronic Cigarette and the Impact of Vaping Ethanol in the Evaluation of Impairment
Third Party Policing: A Randomized Field Trial to Assess Drug Crime Reduction and Police-Hotel Partnerships in Anne Arundel County, MD
Electrochemical Aptamer-Based Sensor for Rapid Identification of Marijuana from Hemp
Phase II Metabolites of Drugs in Hair: A Potential Solution for Environmental Contamination
Real-Time Crime Forecasting Challenge Webinar
This webinar will offer a brief overview of the National Institute of Justice and the data science needs of the criminal justice field. In addition, it will provide details about the Crime Forecasting Challenge, including who can submit, how to retrieve datasets, and the submission categories. The overall goal of the Crime Forecasting Challenge is to harness recent advances in data science to drive innovation in algorithms that advance place-based crime forecasting.
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