Error recovery in cyberphysical digital microfluidic biochips

Droplet-based digital microfluidics technology has now come of age, and software-controlled biochips for healthcare applications are starting to emerge. However, today's digital microfluidic biochips suffer from the drawback that there is no feedback to the control software from the underlying hardware platform. Due to the lack of precision inherent in biochemical experiments, errors are likely during droplet manipulation; error recovery based on the repetition of experiments leads to wastage of expensive reagents and hard-to-prepare samples. By exploiting recent advances in the integration of optical detectors (sensors) into a digital microfluidics biochip, we present a physical-aware system reconfiguration technique that uses sensor data at intermediate checkpoints to dynamically reconfigure the biochip. A cyberphysical resynthesis technique is used to recompute electrode-actuation sequences, thereby deriving new schedules, module placement, and droplet routing pathways, with minimum impact on the time-to-response. © 2012 IEEE.

Chemical and biological applications of digital-microfluidic devices

The advent of digital microfluidic lab-on-a-chip (LoC) technology offers a platform for developing diagnostic applications with the advantages of portability, reduction of the volumes of the sample and reagents, faster analysis times, increased automation, low power consumption, compatibility with mass manufacturing, and high throughput. Moreover, digital microfluidics is being applied in other areas such as airborne chemical detection, DNA sequencing by synthesis, and tissue engineering. In most diagnostic and chemical-detection applications, a key challenge is the preparation of the analyte for presentation to the on-chip detection system. Thus, in diagnostics, raw physiological samples must be introduced onto the chip and then further processed by lysing blood cells and extracting DNA. For massively parallel DNA sequencing, sample preparation can be performed off chip, but the synthesis steps must be performed in a sequential on-chip format by automated control of buffers and nucleotides to extend the read lengths of DNA fragments. In airborne particulate-sampling applications, the sample collection from an air stream must be integrated into the LoC analytical component, which requires a collection droplet to scan an exposed impacted surface after its introduction into a closed analytical section. Finally, in tissue-engineering applications, the challenge for LoC technology is to build high-resolution (less than 10 microns) 3D tissue constructs with embedded cells and growth factors by manipulating and maintaining live cells in the chip platform. This article discusses these applications and their implementation in digital-microfluidic LoC platforms. © 2007 IEEE.

Magnetophoretic circuits for digital control of single particles and cells.

The ability to manipulate small fluid droplets, colloidal particles and single cells with the precision and parallelization of modern-day computer hardware has profound applications for biochemical detection, gene sequencing, chemical synthesis and highly parallel analysis of single cells. Drawing inspiration from general circuit theory and magnetic bubble technology, here we demonstrate a class of integrated circuits for executing sequential and parallel, timed operations on an ensemble of single particles and cells. The integrated circuits are constructed from lithographically defined, overlaid patterns of magnetic film and current lines. The magnetic patterns passively control particles similar to electrical conductors, diodes and capacitors. The current lines actively switch particles between different tracks similar to gated electrical transistors. When combined into arrays and driven by a rotating magnetic field clock, these integrated circuits have general multiplexing properties and enable the precise control of magnetizable objects.

Nested dictionary learning for hierarchical organization of imagery and text

A tree-based dictionary learning model is developed for joint analysis of imagery and associated text. The dictionary learning may be applied directly to the imagery from patches, or to general feature vectors extracted from patches or superpixels (using any existing method for image feature extraction). Each image is associated with a path through the tree (from root to a leaf), and each of the multiple patches in a given image is associated with one node in that path. Nodes near the tree root are shared between multiple paths, representing image characteristics that are common among different types of images. Moving toward the leaves, nodes become specialized, representing details in image classes. If available, words (text) are also jointly modeled, with a path-dependent probability over words. The tree structure is inferred via a nested Dirichlet process, and a retrospective stick-breaking sampler is used to infer the tree depth and width.

Inner speech and bilingual autobiographical memory: a Polish-Danish cross-cultural study.

Thirty years after fleeing from Poland to Denmark, 20 immigrants were enlisted in a study of bilingual autobiographical memory. Ten "early immigrators" averaged 24 years old at the time of immigration, and ten "late immigrators" averaged 34 years old at immigration. Although all 20 had spent 30 years in Denmark, early immigrators reported more current inner speech behaviours in Danish, whereas late immigrators showed more use of Polish. Both groups displayed proportionally more numerous autobiographical retrievals that were reported as coming to them internally in Polish (vs Danish) for the decades prior to immigration and more in Danish (vs Polish) after immigration. We propose a culture- and language-specific shaping of semantic and conceptual stores that underpins autobiographical and world knowledge.

Internal languages of retrieval: the bilingual encoding of memories for the personal past.

In contrast to most research on bilingual memory that focuses on how words in either lexicon are mapped onto memory for objects and concepts, we focus on memory for events in the personal past. Using a word-cue technique in sessions devoted exclusively to one language, we found that older Hispanic immigrants who had come to the United States as adults internally retrieved autobiographical memories in Spanish for events in the country of origin and in English for events in the U.S. These participants were consistently capable of discerning whether a memory had come to them "in words" or not, reflecting the distinction between purely imagistic or conceptual memories and specifically linguistic memories. Via examination of other phenomenological features of these memories (sense of re-living, sensory detail, emotionality, and rehearsal), we conclude that the linguistic/nonlinguistic distinction is fundamental and independent of these other characteristics. Bilinguals encode and retrieve certain autobiographical memories in one or the other language according to the context of encoding, and these linguistic characteristics are stable properties of those memories over time.

A LabVIEW Platform for Preclinical Imaging Using Digital Subtraction Angiography and Micro-CT.

CT and digital subtraction angiography (DSA) are ubiquitous in the clinic. Their preclinical equivalents are valuable imaging methods for studying disease models and treatment. We have developed a dual source/detector X-ray imaging system that we have used for both micro-CT and DSA studies in rodents. The control of such a complex imaging system requires substantial software development for which we use the graphical language LabVIEW (National Instruments, Austin, TX, USA). This paper focuses on a LabVIEW platform that we have developed to enable anatomical and functional imaging with micro-CT and DSA. Our LabVIEW applications integrate and control all the elements of our system including a dual source/detector X-ray system, a mechanical ventilator, a physiological monitor, and a power microinjector for the vascular delivery of X-ray contrast agents. Various applications allow cardiac- and respiratory-gated acquisitions for both DSA and micro-CT studies. Our results illustrate the application of DSA for cardiopulmonary studies and vascular imaging of the liver and coronary arteries. We also show how DSA can be used for functional imaging of the kidney. Finally, the power of 4D micro-CT imaging using both prospective and retrospective gating is shown for cardiac imaging.