Exponent

About: Exponent is a company organization based out in Menlo Park, California, United States. It is known for research contribution in the topics: Population & Risk assessment. The organization has 1589 authors who have published 2680 publications receiving 88140 citations.

Occupational trichloroethylene exposure and non-Hodgkin’s lymphoma: a meta-analysis and review

Abstract: Methods: Meta-analysis and review of 14 occupational cohort and four case-control studies of workers exposed to trichloroethylene (TCE) to investigate the relation between TCE exposure and the risk of non-Hodgkin’s lymphoma (NHL). Studies were selected and categorised based on a priori criteria, and results from random effects meta-analyses are presented. Results: The summary relative risk estimates (SRRE) for the group of cohort studies that had more detailed information on TCE exposure was 1.29 (95% CI 1.00 to 1.66) for the total cohort and 1.59 (95% CI 1.21 to 2.08) for the seven studies that identified a specific TCE exposed sub-cohort. SRREs for three studies with cumulative exposure information were 1.8 (95% CI 0.62 to 5.26) for the lowest exposure category and 1.41 (95% CI 0.61 to 3.23) for the highest category. Comparison of SRREs by levels of TCE exposure did not indicate exposure-response trends. The remaining cohort studies that identified TCE exposure but lacked detailed exposure information had an SRRE of 0.843 (95% CI 0.72 to 0.98). Case-control studies had an SRRE of 1.39 (95% CI 0.62 to 3.10). Statistically significant findings for the Group 1 studies were driven by the results from the subgroup of multiple industry cohort studies (conducted in Europe) (SRRE = 1.86; 95% CI 1.27 to 2.71). The SRRE for single industry cohort studies was not significantly elevated (SRRE = 1.25; 95% CI 0.87 to 1.79). Conclusions: Interpretation of overall findings is hampered by variability in results across the Group 1 studies, limited exposure assessments, lack of evidence of exposure response trends, lack of supportive information from toxicological and mechanistic data, and absence of consistent findings in epidemiologic studies of exposure and NHL. Although a modest positive association was found in the TCE sub-cohort analysis, a finding attributable to studies that included workers from multiple industries, there is insufficient evidence to suggest a causal link between TCE exposure and NHL.

Toward a Taxonomy of Affective Computing

Abstract: Affective computing, which is the topic concerned with the design of emotionally intelligent machines, has been a growing area of interest in the field of human–computer interaction. Many of the current questions in the field will need to be answered in order for progress to be made toward a truly affective computing platform. The current article seeks to summarize much of the existing research in affective computing focused in three primary areas: affective generation, affective understanding, and application. A taxonomy of affective computing applications is then proposed in an effort to help organize the efforts of researchers and designers alike. This taxonomy contains a hierarchy of five tiers: the purpose or goal of the system, the level of integration, the method of affective understanding, the method of affective generation, and the platform of use. The article concludes by highlighting several key issues that the field of affective computing faces moving forward.

Dynamic Battery Modeling of Lead-Acid Batteries using Manufacturers' Data

Abstract: Modeling and simulation of lead acid batteries is of utmost importance in predicting their operation for transportation systems such as hybrid and electric vehicles, for wheelchairs, for battery backup systems such as in UPS for computers and in telecommunication systems. Considerable effort is put into the selection of the appropriate battery model with specific regard to the battery state of charge (SOC) and battery reserve time during the discharge profile for the various different loading conditions expected in the field. This technical paper presents a battery model which uses the manufacturers' data sheet parameters to generate the appropriate terminal voltage and battery capacity for various discharge conditions. This dynamic model is a realistic engineering compromise between model complexity and accuracy and provides parameter flexibility with low simulation times. The results demonstrate that this model provides a reasonable representation of the battery terminal voltage for the different discharge conditions. Due to the relatively long discharge times involved (tens of minutes to an hour at low discharge rates) specific emphasis was placed on high speed modeling and resulting short run times rather than high precision

A vision-based hybrid particle tracking velocimetry (PTV) technique using a modified cascade correlation peak-finding method

Abstract: A novel technique for particle tracking velocimetry is presented in this paper to overcome the issue of overlapping particle images encountered in the flows with high particle density or under volumetric illumination conditions. To achieve this goal, algorithms for particle identification and tracking are developed based on current methods and validated with both synthetic and experimental image sets. The results from synthetic image tests show that the particle identification algorithm is able to resolve overlapped particle images up to 50 % under noisy conditions, while keeping the root mean square peak location error under 0.07 pixels. The algorithm is also robust to the size changes up to a size ratio of 5. The tracking method developed from a classic computer vision matching algorithm is capable of capturing a velocity gradient up to 0.3 while maintaining the error under 0.2 pixels. Sensitivity tests were performed to describe the optimum conditions for the technique in terms of particle image density, particle image sizes and velocity gradients, also its sensitivity to errors of the PIV results that guide the tracking process. The comparison with other existing tracking techniques demonstrates that this technique is able to resolve more vectors out of a dense particle image field.

Utility assessments of opioid treatment for chronic pain.

Abstract: MEDTAP International Inc., Bethesda, Maryland; and § Pain Management Unit, Flinders Medical Centre, South Australia Objective. The primary study objective was to assess preferences for pain treatment outcomes among patients with cancer and noncancer chronic pain. A secondary objective was to assess their quality of life. Methods. Patients with cancer or noncancer chronic pain completed an interview using a computer to estimate utilities, or preference ratings, for health states related to pain treatment. The interview was devised using conjoint analysis methodology. Health states were characterized by four attributes (ef- fectiveness of pain control, side effects, side effect severity, and opioid route of administration) and their levels, and each was assumed to last for a 14-day period. Participants also completed health- related quality of life and demographic questionnaires. Results. Mean preference ratings for participants with noncancer chronic pain (N � 96) ranged from a high of 0.87 (well-controlled pain with no side effects) to a low of 0.18 (poorly controlled pain with severe mood changes/alterations, severe respiratory depression, or severe vomiting). Mean preference ratings for participants with cancer pain (N � 25) were similar and ranged from a high of 0.89 (well- controlled pain with no side effects) to a low of 0.19 (poorly controlled pain with severe respiratory depression or severe vomiting). Results confirmed previous findings that chronic pain has a severe, multidimensional impact on patients, and that the quality of life of persons with chronic pain is among the lowest observed for any medical condition. Conclusions. This study provides a valuable assessment, from the patient's perspective, of the balance between treatment tolerability and manifestation of disease symptoms. Heightened awareness of pa- tients' preferences for treatment outcomes may lead to improved selection of treatments, better ad- herence, and ultimate treatment success.