Design of a remote monitoring and diagnostics platform for air conditioning installations

Includes abstract.Includes bibliographical references (p. 127-129).Faults and inefficiencies in air conditioning installations account for between 2% and 11% of allenergy consumed by commercial buildings in the United States each year. Diagnostics systems havebeen proven to improve the performance of air conditioning plants but the high costs of purchasing,retrofitting and maintaining such a system results in limited market adoption of such systems.This thesis discusses the design, implementation and results of low-cost remote monitoring anddiagnostic platform for use in air conditioning installations. The design of the various hardwarecomponents is presented along with the structure of the framework developed for each device. The thesis also contains information regarding the selection, integration and installation of the various types of sensors required on the various installations. A specially-designed protocol was also developed to handle communication between the hardware devices. Both the physical configuration and details of the protocol structure are presented in detail in this thesis. The mechanism through which the device uploads data to a server is also described in this thesis and includes details on both the hardware and the server technologies used in the upload process. The system has been installed on two different sites in Cape Town, South Africa and has produced meaningful diagnostic information since November 2007

The Q-CHAT (Quantitative CHecklist for Autism in Toddlers): A Normally Distributed Quantitative Measure of Autistic Traits at 18–24 Months of Age: Preliminary Report

We report a major revision of the CHecklist for Autism in Toddlers (CHAT). This quantitative CHAT (Q-CHAT) contains 25 items, scored on a 5 point scale (0-4). The QCHAT was completed by parents of n = 779 unselected toddlers (mean age 21 months) and n = 160 toddlers and preschoolers (mean age 44 months) with an Autism Spectrum Condition (ASC). The ASC group (mean (SD) = 51.8 (14.3)) scored higher on the QCHAT than controls (26.7 (7.8)). Boys in the control group (27.5 (7.8)) scored higher than girls (25.8 (7.7)). The intraclass correlation for test-retest reliability was 0.82 (n=330). The distribution in the control group was close to normal. Full examination of the clinical validity of the Q-CHAT and test properties is underway

Substance use disorders in Iraq and Afghanistan veterans in VA healthcare, 2001–2010: Implications for screening, diagnosis and treatment

Background: The prevalence and correlates of alcohol use disorder (AUD) and drug use disorder (DUD) diagnoses in Iraq and Afghanistan veterans who are new users of Department of Veterans Affairs (VA) healthcare nationwide has not been evaluated. Methods: VA administrative data were used in retrospective cross-sectional descriptive and multivariable analyses to determine the prevalence and independent correlates of AUD and DUD in 456,502 Iraq and Afghanistan veterans who were first-time users of VA healthcare between October 15, 2001 and September 30, 2009 and followed through January 1, 2010. Results: Over 11% received substance use disorder diagnoses: AUD, DUD or both; 10% received AUD diagnoses, 5% received DUD diagnoses and 3% received both. Male sex, age \u3c 25 years, being never married or divorced, and proxies for greater combat exposure were independently associated with AUD and DUD diagnoses. Of those with AUD, DUD or both diagnoses, 55–75% also received PTSD or depression diagnoses. AUD, DUD or both diagnoses were 3–4.5 times more likely in veterans with PTSD and depression (p \u3c 0.001). Conclusions: Post-deployment AUD and DUD diagnoses were more prevalent in subgroups of Iraq and Afghanistan veterans and were highly comorbid with PTSD and depression. Stigma and lack of universal screening may have reduced the number of DUD diagnoses reported. There is a need for improved screening and diagnosis of substance use disorders and increased availability of integrated treatments that simultaneously address AUD and DUD in the context of PTSD and other deployment-related mental health disorders

Face engagement during infancy predicts later face recognition ability in younger siblings of children with autism

Face recognition difficulties are frequently documented in children with autism spectrum disorders (ASD). It has been hypothesized that these difficulties result from a reduced interest in faces early in life, leading to decreased cortical specialization and atypical development of the neural circuitry for face processing. However, a recent study by our lab demonstrated that infants at increased familial risk for ASD, irrespective of their diagnostic status at 3 years, exhibit a clear orienting response to faces. The present study was conducted as a follow-up on the same cohort to investigate how measures of early engagement with faces relate to face-processing abilities later in life. We also investigated whether face recognition difficulties are specifically related to an ASD diagnosis, or whether they are present at a higher rate in all those at familial risk. At 3 years we found a reduced ability to recognize unfamiliar faces in the high-risk group that was not specific to those children who received an ASD diagnosis, consistent with face recognition difficulties being an endophenotype of the disorder. Furthermore, we found that longer looking at faces at 7 months was associated with poorer performance on the face recognition task at 3 years in the high- risk group. These findings suggest that longer looking at faces in infants at risk for ASD might reflect early face-processing difficulties and predicts difficulties with recognizing faces later in life

Face engagement during infancy predicts later face recognition ability in younger siblings of children with autism

Face recognition difficulties are frequently documented in children with autism spectrum disorders (ASD). It has been hypothesized that these difficulties result from a reduced interest in faces early in life, leading to decreased cortical specialization and atypical development of the neural circuitry for face processing. However, a recent study by our lab demonstrated that infants at increased familial risk for ASD, irrespective of their diagnostic status at 3 years, exhibit a clear orienting response to faces. The present study was conducted as a follow-up on the same cohort to investigate how measures of early engagement with faces relate to face-processing abilities later in life. We also investigated whether face recognition difficulties are specifically related to an ASD diagnosis, or whether they are present at a higher rate in all those at familial risk. At 3 years we found a reduced ability to recognize unfamiliar faces in the high-risk group that was not specific to those children who received an ASD diagnosis, consistent with face recognition difficulties being an endophenotype of the disorder. Furthermore, we found that longer looking at faces at 7 months was associated with poorer performance on the face recognition task at 3 years in the high- risk group. These findings suggest that longer looking at faces in infants at risk for ASD might reflect early face-processing difficulties and predicts difficulties with recognizing faces later in life

Infant Neural Sensitivity to Dynamic Eye Gaze relates to quality of parent–infant interaction at 7-months in infants at risk for Autism

Links between brain function measures and quality of parent–child interactions within the early developmental period have been investigated in typical and atypical development. We examined such links in a group of 104 infants with and without a family history for autism in the first year of life. Our findings suggest robust associations between event related potential responses to eye gaze and observed parent–infant interaction measures. In both groups, infants with more positive affect exhibit stronger differentiation to gaze stimuli. This association was observed with the earlier P100 waveform component in the control group but with the later P400 component in infants at-risk. These exploratory findings are critical in paving the way for a better understanding of how infant laboratory measures may relate to overt behavior and how both can be combined in the context of predicting risk or clinical diagnosis in toddlerhood

Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism.

ObjectiveThis is a prospective population screening study for autism in toddlers aged 18-30 months old using the Quantitative Checklist for Autism in Toddlers (Q-CHAT), with follow-up at age 4.DesignObservational study.SettingLuton, Bedfordshire and Cambridgeshire in the UK.Participants13 070 toddlers registered on the Child Health Surveillance Database between March 2008 and April 2009, with follow-up at age 4; 3770 (29%) were screened for autism at 18-30 months using the Q-CHAT and the Childhood Autism Spectrum Test (CAST) at follow-up at age 4.InterventionsA stratified sample across the Q-CHAT score distribution was invited for diagnostic assessment (phase 1). The 4-year follow-up included the CAST and the Checklist for Referral (CFR). All with CAST ≥15, phase 1 diagnostic assessment or with developmental concerns on the CFR were invited for diagnostic assessment (phase 2). Standardised diagnostic assessment at both time-points was conducted to establish the test accuracy of the Q-CHAT.Main outcome measuresConsensus diagnostic outcome at phase 1 and phase 2.ResultsAt phase 1, 3770 Q-CHATs were returned (29% response) and 121 undertook diagnostic assessment, of whom 11 met the criteria for autism. All 11 screened positive on the Q-CHAT. The positive predictive value (PPV) at a cut-point of 39 was 17% (95% CI 8% to 31%). At phase 2, 2005 of 3472 CASTs and CFRs were returned (58% response). 159 underwent diagnostic assessment, including 82 assessed in phase 1. All children meeting the criteria for autism identified via the Q-CHAT at phase 1 also met the criteria at phase 2. The PPV was 28% (95% CI 15% to 46%) after phase 1 and phase 2.ConclusionsThe Q-CHAT can be used at 18-30 months to identify autism and enable accelerated referral for diagnostic assessment. The low PPV suggests that for every true positive there would, however, be ~4-5 false positives. At follow-up, new cases were identified, illustrating the need for continued surveillance and rescreening at multiple time-points using developmentally sensitive instruments. Not all children who later receive a diagnosis of autism are detectable during the toddler period