Potassium-Lead-Switched G-Quadruplexes: A New Class of DNA Logic Gates

A cation-driven allosteric G-quadruplex DNAzyme (PW17) was utilized to devise a conceptually new class of DNA logic gate based on cation-tuned ligand binding and release. K+ favors the binding of hemin to parallel-stranded PW17, thereby promoting the DNAzyme activity, whereas Pb2+ induces PW17 to undergo a parallel-to-antiparallel conformation transition and thus drives hemin to release from the G-quadruplex, deactivating the DNAzyme. Such a K+-Pb2+ switched G-quadruplex, in fact, functions as a two-input INHIBIT logic gate. With the introduction of another input EDTA, this G-quadruplex can be further utilized to construct a reversibly operated IMPLICATION gate.

Calculation formula and synthesis for controlling the composition of hydroxy - Terminated butadiene acrylonitrile cooligomer

In preparing copolymer of the same composition by batch process in two - component copolymerization it is necessary to keep the monomer ratio constant by replenishing the fraction of the more reactive monomer. In this paper a calculation method for monomer feeding is derived, which iscapable of controlling the composition of cooligomer during the course of reaction. Some cooligomers of acrylonitrile and butadiene with relatively the same compositions have been prepared using the replenishing method. The method would be useful for other two - component copolymerization ion process.

PRINCIPLES FOR STRUCTURE GENERATION OF ORGANIC ISOMERS FROM MOLECULAR FORMULA

An expert system for the elucidation of the structure of organic compounds (ESESOC) has been developed. The heart of the ESESOC is formed by the structure generator as an integral part, which receives the specific type of information (molecular formula, s

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

Many-Valued Logic and Qualitative Modelling of Electrical Circuits

Lee M.H., Many-Valued Logic and Qualitative Modelling of Electrical Circuits, in Proc. QR?2000, 14th Int. Workshop on Qualitative Reasoning, Morelia, Mexico June 3rd - 7th 2000.

Application of Inductive Logic Programming to Structure-Based Drug Design

Enot, D. and King, R. D. (2003) Application of Inductive Logic Programming to Structure-Based Drug Design. 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD '03). Springer LNAI 2838 p156-167

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming

Srinivasan, A., King, R. D. and Bain, M.E. (2003) An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. Journal of Machine Learning Research. 4(Jul):369-383

Structure based drug design with inductive logic programming

David P. Enot and Ross D. King (2003). Structure based drug design with inductive logic programming. The ACS National Meeting Spring 2003, New Orleans

The use of Inductive Logic Programming in drug design

David P. Enot and Ross D. King (2002) The use of Inductive Logic Programming in drug design. Proceedings of the 14th EuroQSAR Symposium (EuroQSAR 2002). Blackwell Publishing, p247-250

Giving and Receiving: Nuruddin Farah's Gifts, or, the Postcolonial Logic of Third World Aid

Woods, T. (2003). Giving and Receiving: Nuruddin Farah's Gifts, or, the Postcolonial Logic of Third World Aid. Journal of Commonwealth Literature, 38 (1), 91-112.

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Infant milk formula manufacture: process and compositional interactions in high dry matter wet-mixes

Infant milk formula (IMF) is fortified milk with composition based on the nutrient content in human mother's milk, 0 to 6 months postpartum. Extensive medical and clinical research has led to advances in the nutritional quality of infant formula; however, relatively few studies have focused on interactions between nutrients and the manufacturing process. The objective of this research was to investigate the impact of composition and processing parameters on physical behaviour of high dry matter (DM) IMF systems with a view to designing more sustainable manufacturing processes. The study showed that commercial IMF, with similar compositions, manufactured by different processes, had markedly different physical properties in dehydrated or reconstituted state. Commercial products made with hydrolysed protein were more heat stable compared to products made with intact protein, however, emulsion quality was compromised. Heat-induced denaturation of whey proteins resulted in increased viscosity of wet-mixes, an effect that was dependant on both whey concentration and interactions with lactose and caseins. Expanding on fundamental laboratory studies, a novel high velocity steam injection process was developed whereby high DM (60%) wet-mixes with lower denaturation/viscosity compared to conventional processes could be achieved; powders produced using this process were of similar quality to those manufactured conventionally. Hydrolysed proteins were also shown to be an effective way of reducing viscosity in heat-treated high DM wet-mixes. In particular, using a whey protein concentrate whereby β-Lactoglobulin was selectively hydrolysed, i.e., α-Lactalbumin remained intact, reduced viscosity of wet-mixes during processing while still providing good emulsification. The thesis provides new insights into interactions between nutrients and/or processing which influence physical stability of IMF both in concentrated liquid and powdered form. The outcomes of the work have applications in such areas as; increasing the DM content of spray drier feeds in order to save energy, and, controlling final powder quality.

A mathematical theory of stochastic microlensing. II. Random images, shear, and the Kac-Rice formula

Continuing our development of a mathematical theory of stochastic microlensing, we study the random shear and expected number of random lensed images of different types. In particular, we characterize the first three leading terms in the asymptotic expression of the joint probability density function (pdf) of the random shear tensor due to point masses in the limit of an infinite number of stars. Up to this order, the pdf depends on the magnitude of the shear tensor, the optical depth, and the mean number of stars through a combination of radial position and the star's mass. As a consequence, the pdf's of the shear components are seen to converge, in the limit of an infinite number of stars, to shifted Cauchy distributions, which shows that the shear components have heavy tails in that limit. The asymptotic pdf of the shear magnitude in the limit of an infinite number of stars is also presented. All the results on the random microlensing shear are given for a general point in the lens plane. Extending to the general random distributions (not necessarily uniform) of the lenses, we employ the Kac-Rice formula and Morse theory to deduce general formulas for the expected total number of images and the expected number of saddle images. We further generalize these results by considering random sources defined on a countable compact covering of the light source plane. This is done to introduce the notion of global expected number of positive parity images due to a general lensing map. Applying the result to microlensing, we calculate the asymptotic global expected number of minimum images in the limit of an infinite number of stars, where the stars are uniformly distributed. This global expectation is bounded, while the global expected number of images and the global expected number of saddle images diverge as the order of the number of stars. © 2009 American Institute of Physics.

Muscle Logic: New Knowledge Resource for Anatomy Enables Comprehensive Searches of the Literature on the Feeding Muscles of Mammals.

BACKGROUND: In recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required. DEVELOPMENT AND TESTING OF THE ONTOLOGY: Here we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar. RESULTS AND SIGNIFICANCE: Our tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.