Merging Knowledge Bases in Possibilistic Logic by Lexicographic Aggregation

Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have been proposed to deal with this problem in possibilistic logic, a weighted logic which is powerful for handling inconsistency and deal-ing with uncertainty. They often result in a possibilistic knowledge base which is a set of weighted formulas. Although possibilistic logic is inconsistency tolerant, it suffers from the well-known "drowning effect". Therefore, we may still want to obtain a consistent possibilistic knowledge base as the result of merging. In such a case, we argue that it is not always necessary to keep weighted information after merging. In this paper, we define a merging operator that maps a set of possibilistic knowledge bases and a formula representing the integrity constraints to a classical knowledge base by using lexicographic ordering. We show that it satisfies nine postulates that generalize basic postulates for propositional merging given in [11]. These postulates capture the principle of minimal change in some sense. We then provide an algorithm for generating the resulting knowledge base of our merging operator. Finally, we discuss the compatibility of our merging operator with propositional merging and establish the advantage of our merging operator over existing semantic merging operators in the propositional case.

Programmable motion and separation of single magnetic particles on patterned magnetic surfaces

Motion of single micrometer-sized magnetic particles on patterned magnetic surfaces is controlled by a rotating magnetic field (see Figure and cover). Patterns of thin-film magnetic elements are tailored to form transport lines. Individual particles are separated by adding junctions to the transport lines. The method can improve existing applications in biotechnology and generate new ones in life sciences.

Combining missing-feature theory, speech enhancement, and speaker-dependent/-independent modeling for speech separation

This paper considers the separation and recognition of overlapped speech sentences assuming single-channel observation. A system based on a combination of several different techniques is proposed. The system uses a missing-feature approach for improving crosstalk/noise robustness, a Wiener filter for speech enhancement, hidden Markov models for speech reconstruction, and speaker-dependent/-independent modeling for speaker and speech recognition. We develop the system on the Speech Separation Challenge database, involving a task of separating and recognizing two mixing sentences without assuming advanced knowledge about the identity of the speakers nor about the signal-to-noise ratio. The paper is an extended version of a previous conference paper submitted for the challenge.

Growth of Gold Nanocrystals Incorporated with Magnetic Microbead-based Separation as a Tool for Quantification of Biological Interactions

Au nanoparticles (AuNPs) have been widely used not only as optical labels or ‘weight” labels for the detections of biorecognition events but also an amplifier of surface plasmon resonance biosensors. The intrinsic property of gold nuclei composing of a group of Au atoms to catalyze the reduction of metal ions on the NPs and thereby to enlarge the metallic nanoparticles is employed in different biosensing paths. In a solution containing Au+ ions (e.g. HAuCl4) and the Au clusters, hydrated electrons which are reduced from oxidation of reducers (H2O2, sodium citrate, ascorbic acid, or NaBH4) will be used to reduce the Au+ ion leading to the deposition of Au+ to the Au0 (Au clusters). The reaction will be catalyzed continuously by the Au0 until the Au+ ions and hydrated electrons are exhausted. As a result, the AuNPs will be grown and their optical properties are also changed. If the AuNP nanoclusters are used as probes, the color change will be dependent on amount of analytes, thus give a quantitative monitoring of the analytes.

In this study, we incorporate the use of magnetic beads with the nanocrystalline growth to quantify a target protein based on immunoreactions. Prostate specific antigen (PSA) is chosen as the target analyte because of its values in diagnosis of prostate cancer. A double-sandwiched immunoassay is performed by gold-tagged monoclonal PSA antibody-PSA antigen – magnetic bead-tagged polyclonal PSA antibody interactions. After the immunoreactions, the target analytes are preconcentrated and separated by the magnetic beads while the nanogrowth plays a role of colorimetric signal developer.

The result shows that this is a very sensitive, robust and excellent strategy to detect biological interactions. PSA antigen is detected at femtomolar level with very high specificity under the presence of undesired proteins of crude samples. Furthermore, the method also shows great potential to detect other biological interactions. More details will be described in our presentation.

On the Border of Indeterminacy: The Separation Wall in East Jerusalem

Drawing on a perspective which takes into account the convergences of sovereign and biopolitical ruling apparatuses, the aim of this article is to provide a comprehensive view of the Separation Wall constructed by Israel in East Jerusalem, and, through it, of Israeli control of Palestinian East Jerusalem. Neither a comprehensive border, nor a mere barrier, the Separation Wall which is being constructed in Jerusalem operates to reinstates sovereign power in arrays of governmentality for the purpose of drawing on the ability of sovereignty to appropriate legitimacy for the territorialisation of governmentality. This article claims that these territorialised arrays of governmentality give rise to processes of racialisation, by maintaining a grip on the communities of Palestinians in East Jerusalem and sustaining them in an intermediate position, standing in the way of their full integration into the Israeli population while severing their existing connections with the Palestinians in the West Bank. © Taylor & Francis Group, LLC.

Switching between molecular switch types by module rearrangement:Ca -enabled, H-driven 'off-on-off', H-driven YES and PASS 0 as well as H, Ca-driven AND logic operations

Several logic gates and switches can be accessed from two different combinations of a single set of fluorophore, receptor and spacer components.

A comparative study of biopolymers and alum in the separation and recovery of pulp fibres from paper mill effluent by flocculation

Recovery of cellulose fibres from paper mill effluent has been studied using common polysaccharides or biopolymers such as Guar gum, Xanthan gum and Locust bean gum as flocculent. Guar gum is commonly used in sizing paper and routinely used in paper making. The results have been compared with the performance of alum, which is a common coagulant and a key ingredient of the paper industry. Guar gum recovered about 3.86 mg/L of fibre and was most effective among the biopolymers. Settling velocity distribution curves demonstrated that Guar gum was able to settle the fibres faster than the other biopolymers; however, alum displayed the highest particle removal rate than all the biopolymers at any of the settling velocities. Alum, Guar gum, Xanthan gum and Locust bean gum removed 97.46%, 94.68%, 92.39% and 92.46% turbidity of raw effluent at a settling velocity of 0.5 cm/min, respectively. The conditions for obtaining the lowest sludge volume index such as pH, dose and mixing speed were optimised for guar gum which was the most effective among the biopolymers. Response surface methodology was used to design all experiments, and an optimum operational setting was proposed. The test results indicate similar performance of alum and Guar gum in terms of floc settling velocities and sludge volume index. Since Guar gum is a plant derived natural substance, it is environmentally benign and offers a green treatment option to the paper mills for pulp recycling.

Tailoring Plasmonic Metamaterials for DNA Molecular Logic Gates

Structural and functional information encoded in DNA combined with unique properties of nanomaterials could be of use for the construction of novel biocomputational circuits and intelligent biomedical nanodevices. However, at present their practical applications are still limited by either low reproducibility of fabrication, modest sensitivity, or complicated handling procedures. Here, we demonstrate the construction of label-free and switchable molecular logic gates that use specific conformation modulation of a guanine- and thymine- rich DNA, while the optical readout is enabled by the tunable alphabetical metamaterials, which serve as a substrate for surface enhanced Raman spectroscopy (MetaSERS). By computational and experimental investigations, we present a comprehensive solution to tailor the plasmonic responses of MetaSERS with respect to the metamaterial geometry, excitation energy, and polarization. Our tunable MetaSERS-based DNA logic is simple to operate, highly reproducible, and can be stimulated by ultra-low concentration of the external inputs, enabling an extremely sensitive detection of mercury ions.

Tools for Finding Inconsistencies in Real-world Logic-based Systems

Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.

Logic and Memory Design Based on Unequal Error Protection for Voltage-scalable, Robust and Adaptive DSP Systems

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration block level interactions and ensuring that under any change of operating conditions, only the "less-crucial" computations, that contribute less to block/system output quality, are affected. The proposed approach applies unequal error protection to various blocks of a system-logic and memory-and spans multiple layers of design hierarchy-algorithm, architecture and circuit. The design methodology when applied to a multimedia subsystem shows large power benefits ( up to 69% improvement in power consumption) at reasonable image quality while tolerating errors introduced due to VOS, process variations, and channel noise.