Most mammalian cells (e.g., cancer cells and cardiomyocytes) adhere to a culturing surface. Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a recently developed robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (vs. a few to tens of cells as state-of-the-art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4,000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.

Manipulating single cells with a micropipette is the oldest, yet still a widely used technique. This paper discusses the positioning of a single cell to a target position inside the micropipette after the cell is aspirated into the micropipette. Due to the small volume of a single cell (pico-liter) and nonlinear dynamics involved, this task has high skill requirements and is labor intensive in manual operation that is solely based on trial and error and has high failure rates. We present automated techniques in this paper for achieving this task. Computer vision algorithm was developed to track a single cell inside a micropipette for automated single-cell positioning. A closed-loop robust controller integrating the dynamics of cell motion was designed to accurately and efficiently position the cell to a target position inside the micropipette. The system achieved high success rates of 97% for cell tracking (n=100) and demonstrated its capability of accurately positioning a cell inside the micropipette within 8 seconds (vs. 25 seconds by highly skilled operators).

This paper is the first report of robotic ICSI (intracytoplasmic sperm injection). ICSI is a clinical procedure performed worldwide in fertility clinics, requiring pick-up of a single sperm and insert it into oocyte (i.e., an egg cell). Since its invention 20 years ago, ICSI has been conducted manually by a handful of highly skilled embryologists; however, success rates vary significantly among clinics due to poor reproducibility and inconsistency across operators. We leverage our work in robotic cell injection to realize robotic ICSI and aim ultimately, to standardize how clinical ICSI is performed. This paper presents some of the technical aspects of our robotic ICSI system, including a cell holding device and motion control and computer vision algorithms. The system performs visual tracking of single sperm, robotic immobilization of sperm, aspiration of sperm with pico-liter volume, and insertion of sperm into an oocyte with a high degree of reproducibility. The system requires minimal human involvement (requiring only a few computer mouse clicking), and is human operator skill independent. Using the hamster oocyte-human sperm model in preliminary trials, the robotic system demonstrated a high success rate of 90.0% and survival rate of 90.7% (n=120).

This report proposes a new algorithm for extracting salient regions of videos by introducing two important properties of the early human visual system: (1) Instantaneous saliency depletion with gradual recovery, whereby saliency is instantaneously suppressed and gradually recovered in previously attended regions. (2) Gradual saliency depletion with instantaneous recovery, whereby saliency is gradually decreased over time in non-surprising regions and at the same time recovered in surprising locations. With the introduction of these properties, redundant information in videos can be suppressed and important information is eventually enhanced.

While text-oriented document searching are relatively mature on the Internet, image searching, which requires much more than text matching, significantly lags behind. The use of image search engines significantly enlarges the scope of images to users accessibility. This paper provides an understanding of current technologies in image searching on the Internet, and points to future areas of improvement for multimedia applications. We develop a systematic set of image queries to assess the competence and performance of the major image search engines. We find that current technology is only able to deliver an average precision of around 42% and an average recall of around 12%, while the best performers are capable of producing over 70% for precision and around 27% for recall. The reasons for such differences, and mechanisms for search improvement, are also indicated.

DIMES (Delaware Iterative Multiprocessor Emulation System) is a new FPGA based hardware emulator for large logic systems incorporating a number of identical functional modules such as a Multiprocessor-System-On-Chip or a cellular architecture. It aims to provide both logic verification and early software development environments with dramatically improved cost performance. Under our iterative emulation technology, a part of FPGA resource will be time-shared among several identical modules of the target design and iteratively used to emulate them in multiple steps. The representation of the identical modules in the FPGA consists of (1) a single module copy and (2) a storage block holding all the states of the modules during iterative emulation. On a first implementation of DIMES-called DIMES/P, we have implemented a multiprocessor-system-on-chip design of the IBM Cyclops architecture as a case study. We report our preliminary results and experience of exploiting the iterative emulation technology in Cyclops emulation.

While a significant body of work in compilers has been devoted to reducing energy consumption in embedded systems, the role of a compiler in harnessing the power variation has not been widely explored. Since sharp power variations across time steps cause power supply noises and degrade reliability of functional blocks, power variation is a design constraint in embedded systems. With the advent of high performance embedded systems and extensive deployment of fine grain clock-gating, reducing variations in power is becoming increasingly important.This paper studies how compilation techniques, more specifically instruction scheduling, can ameliorate variations in power due to functional units during program execution. By extending our previous work on rate-optimal software pipelining, this paper formulates the problem of constructing a performance-optimal schedule that minimizes power variations as an integer linear programming (ILP) problem. The formulation can be solved using an ILP solver. We applied our approach on SPEC NAS benchmarks to construct software pipelined schedules that have minimum power variations. The benchmarks are executed on the Wattch power simulator. In comparison to the original (power-unaware) scheduler implemented in the MIPSpro compiler, our power-aware approach generates schedules which have significantly lower power variations while maintaining the same performance. Such schedules have the potential to reduce hardware cost on power delivery in designing embedded systems.