Technology may help overcome nontechnological barriers
Quantum Bridge Analytics relates to methods and systems for hybrid classicalquantum computing, and is devoted to developing tools for bridging classical and quantum computing to gain the benefits of their alliance in the present and enable enhanced practical application of quantum computing in the future.This is the second of a two-part tutorial that surveys key elements of Quantum Bridge Analytics and its applications. Part I focused on the Quadratic Unconstrained Binary Optimization (QUBO) model which is presently the most widely applied optimization model in the quantum computing area, and which unifies a rich variety of combinatorial optimization problems. Part II (the present paper) introduces the domain of QUBO-Plus models that enables a larger range of problems to be handled effectively. After illustrating the scope of these QUBO-Plus models with examples, we give special attention to an important instance of these models called the Asset Exchange Problem (AEP). Solutions to the AEP enable market players to identify exchanges of assets that benefit all participants. Such exchanges are generated by a combination of two optimization technologies for this class of QUBO-Plus models, one grounded in network optimization and one based on a new metaheuristic optimization approach called combinatorial chaining. This combination opens the door to expanding the links to quantum computing applications established by QUBO models through the Quantum Bridge Analytics perspective. We show how the modeling and solution capability for the AEP instance of QUBO-Plus models provides a framework for solving a broad range of problems arising in financial, industrial, scientific, and social settings.
A Xgtll expression library containing cDNA inserts prepared from human placental mRNA was screened immunologically using an antibody probe developed against the ,8-migrating plasminogen activator inhibitor (p-PAI) purified from cultured bovine aortic endothelial cells. Thirty-four positive clones were isolated after screening 7 x i0-phages. Three clones (X1.2, X3, and X9.2) were randomly picked and further characterized. These contained inserts 1.9, 3.0, and 1.9 kilobases (kb) long, respectively. Escherichia coli lysogenic for A9.2, but not for Xgtll, produced a fusion protein of 180 kDa that was recognized by afflinity-purified antibodies against the bovine aortic endothelial cell fl-PAI and had fl-PAI activity when analyzed by reverse fibrin autography. The largest cDNA insert was sequenced and shown to be 2944 base pairs (bp) long. It has a large 3' untranslated region [1788 bp, excluding the poly(A) tail] and contains the entire coding region of the mature protein but lacks the initiation codon and part of the signal peptide coding region at the 5' terminus. The two clones carrying the 1.9-kb cDNA inserts were partially sequenced and shown to be identical to the 3.0-kb cDNA except that they were truncated, lacking much of the 3' untranslated region. Blot hybridization analysis of electrophoretically fractionated RNA from the human fibrosarcoma cell line HT-1080 was performed using the 3.0-kb cDNA as hybridization probe. Two distinct transcripts, 2.2 and 3.0 kb, were detected, suggesting that the 1.9-kb cDNA may have been copied from the shorter RNA transcript. The amino acid sequence deduced from the cDNA was aligned with the NH2-terminal sequence of the human fl-PAL. Based on this alignment, the mature human P-PAI is 379 amino acids long and contains an NH2-terminal valine. The deduced amino acid sequence has extensive (30%) homology with ao-antitrypsin and antithrombin III, indicating that the fl-PAI is a member of the serine proteinase inhibitor (serpin) superfamily. The generation of plasmin from plasminogen provides an important source of proteolytic activity in cells, tissues, and biological fluids (1, 2). Precise regulation of plasminogen activator (PA) activity may thus constitute a critical feature of many biological systems (3). Such control may be at the level of the formation and resolution of fibrin itself (4), at the level of the interaction of PAs with cells (5, 6), or by specific PA inhibitors (PAIs; ref. 7). Available evidence indicates that there are at least three immunologically distinct PAIs, including the placental PAI (8), protease nexin (9), and the endothelial cell-derived PAI (10-12). The PAI synthesized by cultured bovine aortic endothelial cells (BAEs) has been purified and partially characterized (13). It differs from the placental PAI and protease nexin in that it exhibits (B-mobility when analyzed by agarose zone electrophoresis (14). Moreover, it inhibits tissue-type PA (tPA) as well as urokinase-type PA (uPA), whereas protease nexin and the placental PAI are primarily uPA inh...
Quantum Bridge Analytics relates to methods and systems for hybrid classical-quantum computing, and is devoted to developing tools for bridging classical and quantum computing to gain the benefits of their alliance in the present and enable enhanced practical application of quantum computing in the future. This is the second of a two-part tutorial that surveys key elements of Quantum Bridge Analytics and its applications. Part I focused on the Quadratic Unconstrained Binary Optimization (QUBO) model which is presently the most widely applied optimization model in the quantum computing area, and which unifies a rich variety of combinatorial optimization problems. Part II (the present paper) introduces the domain of QUBO-Plus models that enables a larger range of problems to be handled effectively. After illustrating the scope of these QUBO-Plus models with examples, we give special attention to an important instance of these models called the Asset Exchange Problem (AEP). Solutions to the AEP enable market players to identify exchanges of assets that benefit all participants. Such exchanges are generated by a combination of two optimization technologies for this class of QUBO-Plus models, one grounded in network optimization and one based on a new metaheuristic optimization approach called combinatorial chaining. This combination opens the door to expanding the links to quantum computing applications established by QUBO models through the Quantum Bridge Analytics perspective. We show how the modeling and solution capability for the AEP instance of QUBO-Plus models provides a framework for solving a broad range of problems arising in financial, industrial, scientific, and social settings.
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