Multilayer microfluidics based on PDMS (polydimethylsiloxane) soft lithography have offered parallelism and integration for biological and chemical sciences, where reduction in reaction volume and consistency of controlled variables across experiments translate into reduced cost, increased quantity and quality of data. One issue with push up or push down microfluidic control concept is the inability to provide multiple control pressures without adding more complex and expensive external pressure controls. We present here a microfluidic serial DAC (Digital to Analog Converter) that can be integrated with any PDMS device to expand the device's functionality by effectively adding an on-chip pressure regulator. The microfluidic serial DAC can be used with any incompressible fluids and operates in a similar fashion compared to an electronic serial DAC. It can be easily incorporated into any existing multilayer microfluidic devices, and the output pressure that the device generates could be held for extensive times. We explore in this paper various factors that affect resolution, speed, and linearity of the DAC output. As an application, we demonstrate microfluidic DAC's ability for on-chip manipulation of flow resistance when integrated with a simple flow network. In addition, we illustrate an added advantage of using the microfluidic serial DAC in preventing back flow and possible contamination.
New meta-regression methods are introduced that identify whether the magnitude of heterogeneity across study findings is correlated with their standard errors. Evidence from dozens of meta-analyses finds robust evidence of this correlation and that small-sample studies typically have higher heterogeneity. This correlated heterogeneity violates the random-effects (RE) model of additive and independent heterogeneity. When small studies not only have inadequate statistical power but also high heterogeneity, their scientific contribution is even more dubious. When the heterogeneity variance is correlated with the sampling-error variance to the degree we find, simulations show that RE is dominated by an alternative weighted average, the unrestricted weighted least squares (UWLS). Meta-research evidence combined with simulations establish that UWLS should replace RE as the conventional meta-analysis summary of psychological research.
Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Psychiatry HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Psychiatry journal
Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA HomeNew OnlineCurrent IssueFor Authors Podcasts Clinical Reviews Editors' Summary Medical News Author Interviews More Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA journal
This paper proposes two practical approaches to address global convergence failures, commonly encountered in mixed-signal systems in which analog and digital components closely interact. That is, a nominally-working system may fail intermittently depending on its initial conditions upon start-up. The first approach uses a data clustering analysis and verifies global convergence with randomly-selected pilot simulations. The second approach adopts the practice of representing indeterminate states with X by defining its equivalent concept for analog based on entropy. With oscillator and phase-locked loop examples, it is demonstrated that the proposed approaches can effectively detect the failures and guide designers where to add more resets to prevent them.
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
The covariates included within the multivariable models fitted by each paper. This is a data microarray in which the studies run along the Y-axis and the covariates run along the X-axis. Rows and columns are ordered in descending order, based on the total number each covariate was included in the multivariable models fitted by each study. Where patterns were similar between studies or covariates, those studies or covariates were placed next to each other. (PDF 82 kb)
In the context of a recent proposal to exclude research from consideration at the Environmental Protection Agency, John Ioannidis points out that "perceived perfection is not a characteristic of science, but of dogma" and envisions how governments can promote a standard of openness in science.