KANSAS CITY, MO - MARCH 09: Thomas Robinson #0 of the Kansas Jayhawks reacts in their game against the Baylor Bears during the semifinals of the 2012 Big 12 Men's Basketball Tournament.
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In my world, life?s greatest lessons have been learned through a competitive nature and the belief that if failure exists, it came from people who didn?t realize how close they were to success when they gave up.
To me, it is all about focus. If you plan to win, your dedication to the game plan and your desire to be the best you can be must be channeled so that they are not affected by distractions.
It is not easy.
It would be natural to question what significance those words have regarding business and a vibrant municipal economy.
In reply, I heartily emphasize that the lessons learned by children through sponsored youth activities within their city will help mold them into the adults they will become.
An immediate benefit of recreational activities is that they fill unsupervised after-school hours. It has been established that youths are most likely to commit crimes between 2 p.m. and 8 p.m., with crime rates peaking at 3 p.m.
Recreational programs allow youths to connect with adults and other children in their community. Such positive friendships assist children as they grow older.
Sponsored youth programs are designed to fit the personalities and skills of different children. They may include sports, dancing, music, rock climbing, drama, karate, bowling and art.
The economic benefits derived from this sort of curriculum begin with a desired excellent quality of life and factor in a lower crime rate. Corporate CEOs say that quality of life for employees is the third most important factor in deciding where to locate a business.
Youths who participate in structured recreational activities have reduced rates of criminal activity (statistically shown to be by as much as 71 percent), antisocial behavior and increased success in post-secondary education.
These activities can also provide safe, developmental opportunities for latch-key youths, who have reduced prospects for physical activity and socialization because of a lack of parental supervision.
The decrease in the use of emergency services (medical, child welfare, police, fire and so on) and increased proactive use of health promotional services result in lower costs to the taxpayer.
The establishment of positive individual character through involvement in youth recreational activity, as well as economic benefits from a lower crime rate, are paybacks to society.
Steve Curtis has worked as a business consultant and communication specialist. He is currently mayor of Layton.
Source: http://www.standard.net/stories/2012/03/15/communities-benefit-healthy-youth-recreation-programs
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Source: http://www.platinumlogistics.com/wp/logistics-companies-in-lindsay-ca/
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Public release date: 13-Mar-2012
Share ] Contact: Emily Martinez
emily.martinez@utdallas.edu
214-905-3049
University of Texas at Dallas
Recent studies by a UT Dallas researcher aim at finding better ways to diagnose young children with language impairments.
Dr. Christine Dollaghan, a professor at The University of Texas at Dallas Callier Center for Communication Disorders and the School of Behavioral and Brain Sciences, is author of a paper in the Journal of Speech, Language, and Hearing Research. The study evaluated data collected from a large sample of about 600 children. Some of the participants had specific language impairments, or SLI. She wanted to deterimine whether SLI should be regarded as a discrete diagnostic category.
"One of the most basic and long-standing questions about SLI is whether children with the disorder have language skills that differ qualitatively and nonarbitrarily from those of other children or whether their language skills simply fall at the lower end of a continuous distribution, below some arbitrary threshold but not otherwise unique," she wrote in the October article titled "Taxometric Analyses of Specific Language Impairment in 6-Year-Old Children."
Dollaghan previously reported on this sample of children when they were 3 and 4 years old. The new study included some test results that were not available at the earlier ages. She focused on four common indicators of SLI - receptive vocabulary, expressive utterance length, expressive vocabulary diversity and nonsense word repetition.
As in the earlier investigation, she found the 6-year-olds with SLI did not represent a distinct group with unique characteristics Instead, they fell at the lower end of a continuous distribution of language skills.
The results of the study could help in developing diagnostic protocols for children with language impairment and tailoring treatments to the characteristics of individual children. Dollaghan said the categorical-continuous question is being examined by investigators interested in many other diagnostic categories, including autism, schizophrenia and ADHD.
Dollaghan also co-authored an article in the November edition of Artificial Intelligence in Medicine with colleagues from UT Dallas' Erik Jonsson School of Engineering and Computer Science, including lead author Keyur Gabani, Yang Liu and Khairun-nisa Hassanali. The team examined the use of automated machine learning and natural language processing methods for diagnosing language impairment in children based on samples of their language.
In "Exploring a corpus-based approach for detecting language impairment in monolingual English-speaking children," the team reported that automated methods performed well. The findings suggested future collaborations between researchers in computer science and communication disorders will likely be useful, Dollaghan said.
###
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AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.
Public release date: 13-Mar-2012 Share ] Contact: Emily Martinez
emily.martinez@utdallas.edu
214-905-3049
University of Texas at Dallas
Recent studies by a UT Dallas researcher aim at finding better ways to diagnose young children with language impairments.
Dr. Christine Dollaghan, a professor at The University of Texas at Dallas Callier Center for Communication Disorders and the School of Behavioral and Brain Sciences, is author of a paper in the Journal of Speech, Language, and Hearing Research. The study evaluated data collected from a large sample of about 600 children. Some of the participants had specific language impairments, or SLI. She wanted to deterimine whether SLI should be regarded as a discrete diagnostic category.
"One of the most basic and long-standing questions about SLI is whether children with the disorder have language skills that differ qualitatively and nonarbitrarily from those of other children or whether their language skills simply fall at the lower end of a continuous distribution, below some arbitrary threshold but not otherwise unique," she wrote in the October article titled "Taxometric Analyses of Specific Language Impairment in 6-Year-Old Children."
Dollaghan previously reported on this sample of children when they were 3 and 4 years old. The new study included some test results that were not available at the earlier ages. She focused on four common indicators of SLI - receptive vocabulary, expressive utterance length, expressive vocabulary diversity and nonsense word repetition.
As in the earlier investigation, she found the 6-year-olds with SLI did not represent a distinct group with unique characteristics Instead, they fell at the lower end of a continuous distribution of language skills.
The results of the study could help in developing diagnostic protocols for children with language impairment and tailoring treatments to the characteristics of individual children. Dollaghan said the categorical-continuous question is being examined by investigators interested in many other diagnostic categories, including autism, schizophrenia and ADHD.
Dollaghan also co-authored an article in the November edition of Artificial Intelligence in Medicine with colleagues from UT Dallas' Erik Jonsson School of Engineering and Computer Science, including lead author Keyur Gabani, Yang Liu and Khairun-nisa Hassanali. The team examined the use of automated machine learning and natural language processing methods for diagnosing language impairment in children based on samples of their language.
In "Exploring a corpus-based approach for detecting language impairment in monolingual English-speaking children," the team reported that automated methods performed well. The findings suggested future collaborations between researchers in computer science and communication disorders will likely be useful, Dollaghan said.
###
[ | E-mail | Share ] ?
AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.
Source: http://www.eurekalert.org/pub_releases/2012-03/uota-raf030912.php
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