Triangulation in practice

Triangulation is the means by which an alternate perspective is used to validate, challenge or extend existing findings. It is frequently used when the field of study is difficult, demanding or contentious and presence research meets all of these criteria. We distinguish between the use of hard and soft triangulation—the former emphasising the challenging of findings, the latter being more confirmatory in character. Having reviewed a substantial number of presence papers, we conclude that strong triangulation is not widely used while soft triangulation is routinely employed. We demonstrate the usefulness of hard triangulation by contrasting an ontological analysis of in-ness with an empirical study of (computer) game playing. We conclude that presence research would be well served by the wider use of hard triangulation and for the reporting of anomalous and ill-fitting results.

Simulation and fabrication of piezoresistive membrane type MEMS strain sensors

Two piezoresistive (n-polysilicon) strain sensors on a thin Si₃N₄/SiO₂ membrane with improved sensitivity were successfully fabricated by using MEMS technology. The primary difference between the two designs was the number of strips of the polysilicon patterns. For each design, a doped n-polysilicon sensing element was patterned over a thin 3 μm Si₃N₄/SiO₂ membrane. A 1000×1000 μm² window in the silicon wafer was etched to free the thin membrane from the silicon wafer. The intent of this design was to fabricate a flexible MEMS strain sensor similar in function to a commercial metal foil strain gage. A finite element model of this geometry indicates that strains in the membrane will be higher than strains in the surrounding silicon. The values of nominal resistance of the single strip sensor and the multi-strip sensor were 4.6 and 8.6 kΩ, respectively. To evaluate thermal stability and sensing characteristics, the temperature coefficient of resistance [TCR=(ΔR/R₀)/ΔT] and the gage factor [GF=(ΔR/R₀)/] for each design were evaluated. The sensors were heated on a hot plate to measure the TCR. The sensors were embedded in a vinyl ester epoxy plate to determine the sensor sensitivity. The TCR was 7.5×10⁻⁴ and 9.5×10⁻⁴/°C for the single strip and the multi-strip pattern sensors. The gage factor was as high as 15 (bending) and 13 (tension) for the single strip sensor, and 4 (bending) and 21 (tension) for the multi-strip sensor. The sensitivity of these MEMS sensors is much higher than the sensitivity of commercial metal foil strain gages and strain gage alloys.     

Reflected Appraisals, Academic Self-Perceptions, and Math/Science Performance During Early Adolescence.

The authors tested a model of the relations among adolescents' perceptions of parents', teachers', and classmates' support for, valuing of, and beliefs about their competence in math/science; adolescents' own academic self-perceptions concerning math/science; and their academic performance. The sample included 378 middle school students; 65% were Latino, and 21% were European American. Reflected appraisals of adults' beliefs concerning both the importance of and students' competence in math/science, as well as perceived support, predicted students' own self-perceived importance, competence, scholastic behavior, and performance in these courses. Latino students reported lower mean levels of perceived competence than did European American students (controlling for maternal education). Findings have important implications for understanding achievement socialization in ethnically diverse populations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Classification of malnutrition by statistical analysis of quantitative two-dimensional gel electrophoresis of plasma proteins

An attempt to use the relative concentrations of major plasma proteins for clinical assessment of severe malnutrition is described. Quantitative two-dimensional gel electrophoresis was used to measure the concentrations of 24 major proteins in small aliquots of plasma obtained from children, aged 0 to 3 years, who were patients and outpatients in Liberian hospitals. Fifteen had a clinical diagnosis of kwashiorkor, 36 were diagnosed with marasmus, and 18 were controls. There were also 5 controls from the United States. The individuals were placed in six groups; kwashiorkor, kwashiorkor who died during treatment, marasmus, marasmus who died, Liberian controls, and U.S. controls. The amount of protein in each spot in the two-dimensional gels was estimated by measuring bound stain using a laser scanner and computerized image analysis. We found very low serum transferrin levels in malnourishment, in agreement with reports from other investigators. All of the data for 24 protein variables were pooled for factor analysis; the mean factor scores for each group differed, with the kwashiorkor groups furthest from the controls. Results of discriminant analysis using the amounts of different numbers of protein variables (3 to 24) were compared for posterior assignment of individuals to groups. The validity of the method was tested by analysis of plasma aliquots obtained from patients following initiation of therapy and which were not a part of the training set. Predictive performance (prognosis of patient survival) depended upon the number of protein variables used. Although artifactual fitting of the data is expected to contribute to performance as the number of variables is increased, use of as many as 7 variables may be justified, even with our small patient groups. Possible use of these results for development of a practical clinical test is discussed.     

MicroRNAs as Potential Biomarkers in the Differential Diagnosis of Lipomatous Tumors and Their Mimics

Adipocytic tumors are the most common subtype of soft tissue tumors. In current clinical practice, distinguishing benign lipomas from well-differentiated liposarcomas (WDLPS), as well as dedifferentiated liposarcomas (DDLPS) from their morphologic mimics, remains a significant diagnostic challenge. This is especially so when examining small biopsy samples and without the aid of additional ancillary tests. Recognizing the important role that microRNAs (miRNAs) play in tumorigenesis and their potential utility in tumor classification, we analyzed routine clinical tissue samples of benign and malignant lipomatous tumors, as well as other sarcoma mimics, to identify distinguishing miRNA-based signatures that can aid in the differential diagnosis of these entities. We discovered a 6-miRNA signature that separated lipomas from WDLPS with high confidence (AUC of 0.963), as well as a separate 6-miRNA signature that distinguished DDLPS from their more aggressive histologic mimics (AUC of 0.740). Functional enrichment analysis unveiled possible mechanistic involvement of these predictive miRNAs in adipocytic cancer-related biological processes and pathways such as PI3K/AKT/mTOR and MAPK signaling, further supporting the relevance of these miRNAs as biomarkers for adipocytic tumors. Our results demonstrate that miRNA expression profiling may potentially be used as an adjunctive tool for the diagnosis of benign and malignant adipocytic tumors. Further validation studies are warranted.     

Run-to-run control of blood glucose concentrations for people with Type 1 diabetes mellitus

Run-to-run control has been applied to several traditional batch processes in the chemical industry. The 24-h cycle of eating meals, measuring blood glucose concentrations, and delivering the correct insulin bolus, with the goal of achieving the optimal blood glucose profile, can be viewed in the same spirit as traditional batch processes such as emulsion polymerization. In this paper, we aim to exploit the "repetitive" nature of the insulin therapy of people with Type 1 diabetes. A run-to-run algorithm is used on a virtual diabetic patient model to control blood glucose concentrations. The insulin input is parameterized into the timing and amount of the dose while the glucose output is parameterized into the maximum and minimum glucose concentrations. Robustness of the algorithm to variations in the meal amount, meal timing, and insulin sensitivity parameter is addressed. In general, the algorithm is able to converge when the meal timing is varied within +/- 40 min. If the meal size is underestimated by approximately 10 grams (g), the algorithm is able to converge within a reasonable time frame for breakfast, lunch, and dinner. If the meal size is overestimated by 20-25 g, the algorithm is able to converge. When random variations in the meal timing and the meal amount are introduced, the variation on the output variables, Gmax and Gmin, scales according to the amount of variation allowed. Along with this, the insulin sensitivity of the virtual patient model is varied. The algorithm is robust for differences in insulin sensitivity less than +/- 50% of the nominal value.     

InRout - A QoS aware route selection algorithm for industrial wireless sensor networks

Wireless sensor networks are a key enabling technology for industrial monitoring applications where the use of wireless infrastructure allows high adaptivity and low cost in terms of installation and retrofitting. To facilitate the move from the current wired designs to wireless designs, concerns regarding reliability must be satisfied. Current standardization efforts for industrial wireless systems lack specification on efficient routing protocols that mitigate reliability concerns. Consequently, this work presents the InRout route selection algorithm, where local information is shared among neighbouring nodes to enable efficient, distributed route selection while satisfying industrial application requirements and considering sensor node resource limitations. Route selection is described as a multi-armed bandit task and uses Q-learning techniques to obtain the best available solution with low overhead. A performance comparison with existing approaches demonstrates the benefits of the InRout algorithm, which satisfies typical quality of service requirements for industrial monitoring applications while considering sensor node resources. Simulation results show that InRout can provide gains ranging from 4% to 60% in the number of successfully delivered packets when compared to current approaches with much lower control overhead.