Modular droplet actuator drive

A droplet actuator drive including a detection apparatus for sensing a property of a droplet on a droplet actuator; circuitry for controlling the detection apparatus electronically coupled to the detection apparatus; a droplet actuator cartridge connector arranged so that when a droplet actuator cartridge electronically is coupled thereto: the droplet actuator cartridge is aligned with the detection apparatus; and the detection apparatus can sense the property of the droplet on a droplet actuator; circuitry for controlling a droplet actuator coupled to the droplet actuator connector; and the droplet actuator circuitry may be coupled to a processor

Maximum Mean Discrepancy Meets Neural Networks: The Radon-Kolmogorov-Smirnov Test

Maximum mean discrepancy (MMD) refers to a general class of nonparametric two-sample tests that are based on maximizing the mean difference over samples from one distribution $P$ versus another $Q$, over all choices of data transformations $f$ living in some function space $\mathcal{F}$. Inspired by recent work that connects what are known as functions of $\textit{Radon bounded variation}$ (RBV) and neural networks (Parhi and Nowak, 2021, 2023), we study the MMD defined by taking $\mathcal{F}$ to be the unit ball in the RBV space of a given smoothness order $k \geq 0$. This test, which we refer to as the $\textit{Radon-Kolmogorov-Smirnov}$ (RKS) test, can be viewed as a generalization of the well-known and classical Kolmogorov-Smirnov (KS) test to multiple dimensions and higher orders of smoothness. It is also intimately connected to neural networks: we prove that the witness in the RKS test -- the function $f$ achieving the maximum mean difference -- is always a ridge spline of degree $k$, i.e., a single neuron in a neural network. This allows us to leverage the power of modern deep learning toolkits to (approximately) optimize the criterion that underlies the RKS test. We prove that the RKS test has asymptotically full power at distinguishing any distinct pair $P \not= Q$ of distributions, derive its asymptotic null distribution, and carry out extensive experiments to elucidate the strengths and weakenesses of the RKS test versus the more traditional kernel MMD test

Droplet microactuator system

The present invention relates to a droplet microactuator system. According to one embodiment, the droplet microactuator system includes: (a) a droplet microactuator configured to conduct droplet operations; (b) a magnetic field source arranged to immobilize magnetically responsive beads in a droplet during droplet operations; (c) a sensor configured in a sensing relationship with the droplet microactuator, such that the sensor is capable of sensing a signal from and/or a property of one or more droplets on the droplet microactuator; and (d) one or more processors electronically coupled to the droplet microactuator and programmed to control electrowetting-mediated droplet operations on the droplet actuator and process electronic signals from the sensor

Systems, methods, and products for graphically illustrating and controlling a droplet actuator

Systems for controlling a droplet microactuator are provided. According to one embodiment, a system is provided and includes a controller, a droplet microactuator electronically coupled to the controller, and a display device displaying a user interface electronically coupled to the controller, wherein the system is programmed and configured to permit a user to effect a droplet manipulation by interacting with the user interface. According to another embodiment, a system is provided and includes a processor, a display device electronically coupled to the processor, and software loaded and/or stored in a storage device electronically coupled to the controller, a memory device electronically coupled to the controller, and/or the controller and programmed to display an interactive map of a droplet microactuator. According to yet another embodiment, a system is provided and includes a controller, a droplet microactuator electronically coupled to the controller, a display device displaying a user interface electronically coupled to the controller, and software for executing a protocol loaded and/or stored in a storage device electronically coupled to the controller, a memory device electronically coupled to the controller, and/or the controller

Digital Microfluidics Sample Analyzer

Three innovations address the needs of the medical world with regard to microfluidic manipulation and testing of physiological samples in ways that can benefit point-of-care needs for patients such as premature infants, for which drawing of blood for continuous tests can be life-threatening in their own right, and for expedited results. A chip with sample injection elements, reservoirs (and waste), droplet formation structures, fluidic pathways, mixing areas, and optical detection sites, was fabricated to test the various components of the microfluidic platform, both individually and in integrated fashion. The droplet control system permits a user to control droplet microactuator system functions, such as droplet operations and detector operations. Also, the programming system allows a user to develop software routines for controlling droplet microactuator system functions, such as droplet operations and detector operations. A chip is incorporated into the system with a controller, a detector, input and output devices, and software. A novel filler fluid formulation is used for the transport of droplets with high protein concentrations. Novel assemblies for detection of photons from an on-chip droplet are present, as well as novel systems for conducting various assays, such as immunoassays and PCR (polymerase chain reaction). The lab-on-a-chip (a.k.a., lab-on-a-printed-circuit board) processes physiological samples and comprises a system for automated, multi-analyte measurements using sub-microliter samples of human serum. The invention also relates to a diagnostic chip and system including the chip that performs many of the routine operations of a central labbased chemistry analyzer, integrating, for example, colorimetric assays (e.g., for proteins), chemiluminescence/fluorescence assays (e.g., for enzymes, electrolytes, and gases), and/or conductometric assays (e.g., for hematocrit on plasma and whole blood) on a single chip platform

Droplet actuator analyzer with cartridge

A droplet actuator with cartridge is provided. According to one embodiment, a sample analyzer is provided and includes an analyzer unit comprising electronic or optical receiving means, a cartridge comprising self-contained droplet handling capabilities, and a wherein the cartridge is coupled to the analyzer unit by a means which aligns electronic and/or optical outputs from the cartridge with electronic or optical receiving means on the analyzer unit. According to another embodiment, a sample analyzer is provided and includes a sample analyzer comprising a cartridge coupled thereto and a means of electrical interface and/or optical interface between the cartridge and the analyzer, whereby electrical signals and/or optical signals may be transmitted from the cartridge to the analyzer

Terminology of metal–organic frameworks and coordination polymers (IUPAC Recommendations 2013)

A set of terms, definitions, and recommendations is provided for use in the classification of coordination polymers, networks, and metal–organic frameworks (MOFs). A hierarchical terminology is recommended in which the most general term is coordination polymer. Coordination networks are a subset of coordination polymers and MOFs a further subset of coordination networks. One of the criteria an MOF needs to fulfill is that it contains potential voids, but no physical measurements of porosity or other properties are demanded per se. The use of topology and topology descriptors to enhance the description of crystal structures of MOFs and 3D-coordination polymers is furthermore strongly recommended

Does Medical Malpractice Law Improve Health Care Quality?

Despite the fundamental role of deterrence in justifying a system of medical malpractice law, surprisingly little evidence has been put forth to date bearing on the relationship between medical liability forces on the one hand and medical errors and health care quality on the other. In this paper, we estimate this relationship using clinically validated measures of health care treatment quality constructed using data from the 1979 to 2005 National Hospital Discharge Surveys and the 1987 to 2008 Behavioral Risk Factor Surveillance System records. Drawing upon traditional, remedy-centric tort reforms — e.g., damage caps — we estimate that the current liability system plays at most a modest role in inducing higher levels of health care quality. We contend that this limited independent role for medical liability may be a reflection upon the structural nature of the present system of liability rules, which largely hold physicians to standards determined according to industry customs. We find evidence suggesting, however, that physician practices may respond more significantly upon a substantive alteration of this system altogether — i.e., upon a change in the clinical standards to which physicians are held in the first instance. The literature to date has largely failed to appreciate the substantive nature of liability rules and may thus be drawing limited inferences based solely on our experiences to date with damage-caps and related reforms