Deadlock detection in distributed database systems: a new algorithm and a comparative performance analysis

This paper attempts a comprehensive study of deadlock detection in distributed database systems. First, the two predominant deadlock models in these systems and the four different distributed deadlock detection approaches are discussed. Afterwards, a new deadlock detection algorithm is presented. The algorithm is based on dynamically creating deadlock detection agents (DDAs), each being responsible for detecting deadlocks in one connected component of the global wait-for-graph (WFG). The DDA scheme is a “self-tuning” system: after an initial warm-up phase, dedicated DDAs will be formed for “centers of locality”, i.e., parts of the system where many conflicts occur. A dynamic shift in locality of the distributed system will be responded to by automatically creating new DDAs while the obsolete ones terminate. In this paper, we also compare the most competitive representative of each class of algorithms suitable for distributed database systems based on a simulation model, and point out their relative strengths and weaknesses. The extensive experiments we carried out indicate that our newly proposed deadlock detection algorithm outperforms the other algorithms in the vast majority of configurations and workloads and, in contrast to all other algorithms, is very robust with respect to differing load and access profiles. Received December 4, 1997 / Accepted February 2, 1999     

Visual Homing: Surfing on the Epipoles

We introduce a novel method for visual homing. Using this method a robot can be sent to desired positions and orientations in 3D space specified by single images taken from these positions. Our method is based on recovering the epipolar geometry relating the current image taken by the robot and the target image. Using the epipolar geometry, most of the parameters which specify the differences in position and orientation of the camera between the two images are recovered. However, since not all of the parameters can be recovered from two images, we have developed specific methods to bypass these missing parameters and resolve the ambiguities that exist. We present two homing algorithms for two standard projection models, weak and full perspective.Our method determines the path of the robot on-line, the starting position of the robot is relatively not constrained, and a 3D model of the environment is not required. The method is almost entirely memoryless, in the sense that at every step the path to the target position is determined independently of the previous path taken by the robot. Because of this property the robot may be able, while moving toward the target, to perform auxiliary tasks or to avoid obstacles, without this impairing its ability to eventually reach the target position. We have performed simulations and real experiments which demonstrate the robustness of the method and that the algorithms always converge to the target pose.     

Ultra-Small ATP-Decorated Gold Nanoparticles for Targeting Amyloid Fibrils in Neurodegenerative Diseases

Ultrafine Gold nanoparticles (Au NPs) functionalized with various biomolecules constitute an alternative to antibodies as anti-amyloidogenic agents. However, generating stable ultrafine Au NPs with high surface activity is challenging. Here, the capacity of phosphate groups in biomolecules is used to stabilize Au NPs. The characteristics of Au NPs decorated with adenosine mono-, di-, and tri-phosphate are compared as well as adenosine and peptide nucleic acid-containing adenosine as controls. Among them, ATP-Au NPs are found to be superior having small size (2–4 nm) and stability (for several months) when analysed by spectroscopy and electron microscopy. Spectroscopy analysis also revealed that each ATP-stabilized Au NP is decorated with 7–8 molecules of ATP. ThT binding analysis and TEM imaging showed that the ATP-Au NPs efficiently prevented amyloid fibril formation in vitro by Aβ-42, α-Synuclein as well as by the Glucosylceramide metabolite, and disaggregated their pre-formed fibrils. NMR analysis revealed the interaction of the ATP-Au NPs with the amyloid fibrils. The ATP-Au NPs are safe toward cultured SH-SY5Y cells and when co-incubated with α-Synuclein amyloids inhibited their cytotoxicity and readily enter the cells to inhibit formation of amyloid fibrils within them. The results indicates the pharmacological potentials of ATP decorated Au NPs.     

Innovations in the ENHS reactor design and fuel cycle

A number of approaches were explored for improving characteristics of the encapsulated nuclear heat source (ENHS) reactor and its fuel cycle, including: increasing the ENHS module power, power density and the specific power, making the core design insensitive to the actinides composition variation with number of fuel recycling and reducing the positive void coefficient of reactivity. Design innovations examined for power increase include intermediate heat exchanger (IHX) design optimization, riser diameter optimization, introducing a flow partition inside the riser, increasing the cooling time of the LWR discharged TRU, increasing the minor actinides' concentration in the loaded fuel and split-enrichment for power flattening. Another design innovation described utilizes a unique synergism between the use of MA and the design of reduced power ENHS cores.

Also described is a radically different ENHS reactor concept that has a solid core from which heat pipes transport the fission power to a coolant circulating around the reflector. Promising features of this design concept include enhanced decay heat removal capability; no positive void reactivity coefficient; no direct contact between the fuel clad and the coolant; a core that is more robust for transportation; higher coolant temperature potentially offering higher energy conversion efficiency and hydrogen production capability.     

Robust real-time unusual event detection using multiple fixed-location monitors

We present a novel algorithm for detection of certain types of unusual events. The algorithm is based on multiple local monitors which collect low-level statistics. Each local monitor produces an alert if its current measurement is unusual, and these alerts are integrated to a final decision regarding the existence of an unusual event. Our algorithm satisfies a set of requirements that are critical for successful deployment of any large-scale surveillance system. In particular it requires a minimal setup (taking only a few minutes) and is fully automatic afterwards. Since it is not based on objects' tracks, it is robust and works well in crowded scenes where tracking-based algorithms are likely to fail. The algorithm is effective as soon as sufficient low-level observations representing the routine activity have been collected, which usually happens after a few minutes. Our algorithm runs in realtime. It was tested on a variety of real-life crowded scenes. A ground-truth was extracted for these scenes, with respect to which detection and false-alarm rates are reported.