Propagation of Delay in Probabilistic CMOS Systems

Future low voltage noise dominated designs render probabilistic behavior of CMOS. This is acceptable as far as applications’ intrinsic error resilience allows quantified inaccuracy in results to save energy consumption, such as in applications like audio/video processing and sky image formation in radio astronomy. This introduces the trade-off between energy consumption (E) and probability of correctness (p) that provides an opportunity for inexact computing to attain higher energy efficiency. Efforts have been made in the last decade to model probabilistic CMOS (PCMOS) keeping in view the noise variance and to establish its feasibility for error resilient applications focused on the nominal voltage range. However, exploiting the near threshold voltage (NTV) range is quite a promising energy efficient design technique that operates the hardware at relatively slower pace while retaining the deterministic property of computations. We propose to take the advantage of energy efficiency at NTV while retaining the speed as constant, sacrificing p to the extent allowed by applications resilience. In this regard, we investigated the impact of NTV operation on PCMOS where more energy can be saved with less accurate results. Our simulation results of an inverter and a 4-bit ripple carry adder in Cadence showed the shortcomings of current analytical models for probability of correctness at NTV and lower voltage supplies. We further investigated the impact of delay propagation in a digital system composed of probabilistic building blocks, which provides a clear insight of timing delay affecting the higher significant computational bits more than its lower significant counterparts and hence contributing considerably to the total error

MO4 - Using AHP weights to fill missing gaps in Markov decision models

OBJECTIVES:\ud We propose to combine the versatility of the analytic hierarchy process (AHP) with the decision-analytic sophistication of health-economic modeling in a new methodology for early technology assessment. As an illustration, we apply this methodology to a new technology to diagnose breast cancer.\ud \ud METHODS:\ud The AHP is a technique for multicriteria analysis, relatively new in the fi eld of technology assessment. It can integrate both quantitative and qualitative criteria in the assessment of alternative technologies. We applied the AHP to prioritize a more versatile set of outcome measures than most Markov models do. These outcome measures include clinical effectiveness and costs, but also weighted estimates of patient comfort and safety. Furthermore, as no clinical data are available for this technology yet, the AHP is applied to predict the performance of the new technology with regard to all these outcome measures. Results of the AHP are subsequently integrated in a Markov model to make an early assessment of the expected incremental cost-effectiveness of alternative technologies.\ud \ud RESULTS:\ud We systematically estimated priors on the clinical effectiveness and wider impacts of the new technology using AHP. In our illustration, AHP estimates for sensitivity and specifi city of the new diagnostic technology were used as probability parameters in the Markov model. Moreover, the prioritized outcome measures including clinical effectiveness (weight = 0.61), patient comfort (weight = 0.09), and safety (weight = 0.30) were integrated into one outcome measure in the Markov model.\ud \ud CONCLUSIONS:\ud Combining AHP and Markov modelling is particularly valuable in early technology assessment when evidence about the effectiveness of health care technology is still limited or missing. Moreover, combining these methods is valuable when decision makers are interested in other patient relevant outcomes measures besides the technology’s clinical effectiveness, and that may not (adequately or explicitly) be captured in mainstream utility measures

eHealth in the support of people with mild intellectual disability in daily life:A systematic review

Background:  eHealth has recently made rapid progress in care, support and treatment. However, studies on the use of eHealth to support people with a mild intellectual disability in daily life are limited. A systematic review was conducted to provide an overview of this use of eHealth.  Methods:  Seven databases were searched for relevant studies and assessed according to the PRISMA guidelines. Descriptive analyses were deployed using the Matching Person to Technology model to evaluate the key areas contributing to successful eHealth use.  Results:  Most of the 46 studies included were small-scale case studies and focused on using eHealth to acquire daily living skills and vocational skills. In addition, several studies focused on eHealth use for self-support in daily living, and three studies focused on remote professional support.  Conclusions:  eHealth offers opportunities to support people with mild intellectual disability in various different contexts of daily life. Scientific research on this topic is in its early stage, and further high-quality research is needed

The influence of different intermittent myofeedback training schedules on learning relaxation of the trapezius muscle while performing a gross-motor task

The aim of this study was to investigate the influence of different intermittent myofeedback training schedules, as provided by a Cinderella-based myofeedback system, on learning relaxation and resistance to extinction of the trapezius muscle, in subjects performing a unilateral gross-motor task. Eighteen healthy subjects performed the task without and with feedback to study baseline and learning relaxation. Subsequently, resistance to extinction was investigated by performing the task without feedback. The gross-motor task consisted of continuously moving the dominant arm between three target areas at a constant pace. Subjects were randomly assigned into three groups, characterized by the sequence of feedback schedules with which the task was performed on 3 consecutive days. Auditory feedback was provided after a 5-, 10-, or 20-s interval when a pre-set level of 80% rest was not reached. Bipolar surface electromyography recordings performed at the dominant upper trapezius muscle were quantified using relative rest time (RRT) and root mean square (RMS) parameters. Learning relaxation was defined as an increase in RRT and a decrease in RMS values. Results showed the highest RRT levels as well as a decrease in RMS for the 10-s schedule. Additionally, the 10-s schedule was unique in its ability to elevate muscular rest above the 20% level, which may be considered relevant in preventing myalgia. None of the three schedules showed resistance to extinction. It was concluded that the 10-s interval was preferred over the 5- and 20-s schedules in learning trapezius relaxation in subjects performing a unilateral gross-motor task

Association between CTL Precursor Frequency to HLA-C Mismatches and HLA-C Antigen Cell Surface Expression

Previous studies showed the relevance of the cytotoxic T-cell precursor (CTLp) frequency assay for prediction of the outcome of HLA mismatched hematopoietic cell transplantation (HCT). Recently, it has been shown that HLA-C cell surface expression is correlated with virus specific cytotoxic T-cell responses and viremia control in HIV patients. The aim of the current study was to investigate the association between HLA-C antigen expression and the CTLp frequency to the mismatched HLA-C antigen. In total 115 recipient–donor pairs, for whom a successful CTLp assay was performed, were evaluated for this pilot study. All donor–recipient pairs were matched at 9/10 alleles with a single mismatch at the HLA-C locus. Antigen expression level of the mismatched HLA-C allele for each recipient and donor was based on the mean fluorescence intensity (MFI) values as described by Apps et al. (1). The cell surface expression of recipient’s mismatched HLA-C antigen was significantly lower among CTLp negative (n = 59) compared to CTLp positive (n = 56) pairs (154 and 193 MFI units, respectively, p = 0.0031). This difference was more pronounced in donor–recipient pairs that were mismatched for amino-acid residue-116 located in the groove of the HLA-C antigen, suggesting that the importance of peptide binding in the allo-recognition. Furthermore, in the particular case of low expression of the recipient mismatched HLA-C antigen (MFI < 115), CTLp reactivity depended on HLA-C expression level in the donor, the median MFI of donor’s mismatched HLA-C antigen was 114 in CTLp negative cases (n = 26), while in CTLp positive cases (n = 15) the median MFI of donor’s HLA-C antigen was 193 (p = 0.0093). We conclude that the expression level of the donor and recipient mismatched HLA-C antigens affect CTLp outcome. HLA-C antigen expression levels in combination with the CTLp assay may prove useful for the prediction of the clinical outcome of HLA-C mismatched HCT

Characteristics of innovators adopting a national personal health record in Portugal : cross-sectional study

©Liliana Laranjo, Inês Rodolfo, Ana Marta Pereira, Armando Brito de Sá. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 11.10.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.Background: Personal health records (PHRs) are increasingly being deployed worldwide, but their rates of adoption by patients vary widely across countries and health systems. Five main categories of adopters are usually considered when evaluating the diffusion of innovations: innovators, early adopters, early majority, late majority, and laggards. Objective: We aimed to evaluate adoption of the Portuguese PHR 3 months after its release, as well as characterize the individuals who registered and used the system during that period (the innovators). Methods: We conducted a cross-sectional study. Users and nonusers were defined based on their input, or not, of health-related information into the PHR. Users of the PHR were compared with nonusers regarding demographic and clinical variables. Users were further characterized according to their intensity of information input: single input (one single piece of health-related information recorded) and multiple inputs. Multivariate logistic regression was used to model the probability of being in the multiple inputs group. ArcGis (ESRI, Redlands, CA, USA) was used to create maps of the proportion of PHR registrations by region and district. Results: The number of registered individuals was 109,619 (66,408/109,619, 60.58% women; mean age: 44.7 years, standard deviation [SD] 18.1 years). The highest proportion of registrations was observed for those aged between 30 and 39 years (25,810/109,619, 23.55%). Furthermore, 16.88% (18,504/109,619) of registered individuals were considered users and 83.12% (91,115/109,619) nonusers. Among PHR users, 32.18% (5955/18,504) engaged in single input and 67.82% (12,549/18,504) in multiple inputs. Younger individuals and male users had higher odds of engaging in multiple inputs (odds ratio for male individuals 1.32, CI 1.19-1.48). Geographic analysis revealed higher proportions of PHR adoption in urban centers when compared with rural noncoastal districts. Conclusions: Approximately 1% of the country’s population registered during the first 3 months of the Portuguese PHR. Registered individuals were more frequently female aged between 30 and 39 years. There is evidence of a geographic gap in the adoption of the Portuguese PHR, with higher proportions of adopters in urban centers than in rural noncoastal districts.This work was supported by a Junior Clinical Research award from the Harvard Medical School—Portugal program (HMSP-ICJ/0005/2010; Fundação para a Ciência e Tecnologia) attributed to the first author.info:eu-repo/semantics/publishedVersio

STS in management education: connecting theory and practice

This paper explores the value of science and technology studies (STS) to management education. The work draws on an ethnographic study of second year management undergraduates studying decision making. The nature and delivery of the decision making module is outlined and the value of STS is demonstrated in terms of both teaching method and module content. Three particular STS contributions are identified and described: the social construction of technological systems; actor network theory; and ontological politics. Affordances and sensibilities are identified for each contribution and a discussion is developed that illustrates how these versions of STS are put to use in management education. It is concluded that STS has a pivotal role to play in critical management (education) and in the process offers opportunities for new forms of managin

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p