Revisiting Synthesis for One-Counter Automata

We study the (parameter) synthesis problem for one-counter automata with parameters. One-counter automata are obtained by extending classical finite-state automata with a counter whose value can range over non-negative integers and be tested for zero. The updates and tests applicable to the counter can further be made parametric by introducing a set of integer-valued variables called parameters. The synthesis problem for such automata asks whether there exists a valuation of the parameters such that all infinite runs of the automaton satisfy some omega-regular property. Lechner showed that (the complement of) the problem can be encoded in a restricted one-alternation fragment of Presburger arithmetic with divisibility. In this work (i) we argue that said fragment, called AERPADPLUS, is unfortunately undecidable. Nevertheless, by a careful re-encoding of the problem into a decidable restriction of AERPADPLUS, (ii) we prove that the synthesis problem is decidable in general and in N2EXP for several fixed omega-regular properties. Finally, (iii) we give a polynomial-space algorithm for the special case of the problem where parameters can only be used in tests, and not updates, of the counter

Alternative institutional arrangements for contract farming in poultry production in Bangladesh and their impacts on equity

Also available in the ILRI Repository on Livestock Research at http://hdl.handle.net/10568/217Livestock Production/Industries,

Cleavage of Ge–S and C–H bonds in the reaction of electron-deficient [Os₃(CO)₈(μ-H)(μ₃-Ph₂PCH₂P(Ph)C₆H₄)] with Ph₃GeSPh: Generation of thiophenol derivatives [Os₃(CO)₈(μ-H)(μ-SPh)(μ-dppm)] and [Os₃(CO)₇(μ-H)(μ-SPh)(μ₃-SC₆H₄)(μ-dppm)]

Heating the electron-deficient [Os₃(CO)₈(μ-H)(μ₃-Ph₂PCH₂P(Ph)C₆H₄)] (1) and Ph₃GeSPh in benzene at 80 °C led to the thiolato bridged compounds, [Os₃(CO)₈(μ-H)(μ-SPh)(μ-dppm)] (2) and [Os₃(CO)₇(μ-H)(μ-SPh)(μ₃-SC₆H₄)(μ-dppm)] (3), formed by cleavage of Ge–S and C–S bonds of the ligand, in 40% and 17% yields, respectively. Both compounds 2 and 3 have been characterized by a combination of elemental analysis, infrared and ¹H NMR spectroscopic data together with single crystal X-ray crystallography. Compound 3 contains an open triangle of osmium atoms bridged by a SPh and SC₆H₄ ligands on opposite sides of the cluster with a dppm ligand bridging one of the Os–Os edges. Compound 2 consists of a closed triangular cluster of osmium atoms with a bridging SPh, and a bridging hydride ligand on the same Os–Os edge, and a dppm ligand bridging one of the remaining Os–Os edges

Expression and cellular localization of hepcidin mRNA and protein in normal rat brain

Abstract Background Hepcidin is a peptide hormone belonging to the defensin family of cationic antimicrobial molecules that has an essential role in systemic iron homeostasis. The peptide is synthesised by hepatocytes and transported in the circulation to target tissues where it regulates the iron export function of the ferrous iron permease, ferroportin. In the brain hepcidin protein has been identified using immuno-histochemistry and mRNA by real-time PCR but not by in situ hybridisation raising the question of whether there is measurable transcription of the hepcidin gene in the central nervous system. Alternatively hepcidin could be transported as a hormone to the brain via the circulation. Results By RT-PCR hepcidin mRNA was present at low level throughout normal rat brain while in situ hybridisation to detect low-abundant mRNA revealed that transcripts were restricted to endothelium of blood vessels and choroid plexus. In contrast, hepcidin protein analysed by immuno-histochemistry was highly expressed in blood vessels, in endothelium and in pericytes. Hepcidin was also present in glial cells and in the olfactory bulb, sub-ventricular zone and dentate gyrus, areas where neurogenesis and synaptic plasticity are maintained throughout adult life. The hepcidin species identified by Western blotting in sub-ventricular zone, cortex and hippocampus migrated as a ~2.8 kDa band, identical in size to hepcidin present in normal rat serum suggesting that hepcidin in brain was the full-length biologically active 25 amino acid peptide. Hepcidin co-localised with ferroportin in ependymal cells of the sub-ventricular zone and in the corpus callosum consistent with a regulatory role in iron metabolism at these sites. Conclusions Hepcidin protein was widely expressed in brain parenchyma while levels of hepcidin gene transcription appeared to be below the limits of detection of the in situ hybridisation probes. This disparity suggests that not all hepcidin in the brain is transcribed in situ and may originate in part outside the brain. The properties of hepcidin as a cationic peptide hormone are reflected in the finding of hepcidin in the walls of blood vessels and in pericytes and glia, cells that may be involved in transporting the peptide into brain interstitium

General Relativistic effects on the conversion of nuclear to two-flavour quark matter in compact stars

We investigate the General Relativistic (GR) effects on the conversion from nuclear to two-flavour quark matter in compact stars, both static as well as rotating. We find that GR effects lead to qualitative differences in rotating stars, indicating the inadequacy of non-relativistic (NR) or even Special Relativistic (SR) treatments for these cases.Comment: 4 pages, 4 figure

Auto-detection interpretation model for horizontal oil wells using pressure transient responses

Directional drilling is an excellent option to extend the limited reservoir reach and contact offered by vertical wells. Pressure transient responses (PTR) of horizontal wells provide key information about the reservoirs drilled. In this study multilayer perceptron (MLP) neural networks are used to correctly identify reservoir models from pressure derivative curves derived from horizontal wells. To this end, 2560 pressure derivative curves for six distinct reservoir models are generated and used to design a machine-learning classifier. A single hidden layer MLP network with 5 neurons, trained with a scaled conjugate gradient algorithm, is selected as the best classifier. This smart classifier provides total classification accuracy of 98.3%, mean square error of 0.00725, and coefficient of determination of 0.97332 over the whole dataset. Performance accuracy of the proposed classifier is verified with real field data, synthetically generated noisy PTR, and some signals outside the range initially assessed by the training plus testing data subsets. The developed network can correctly identify the reservoir-flow model with a probability of close to 0.9. The novelty of this work is that it employs a large dataset of horizontal (not vertical) well tests applied to six reservoir-flow models and includes noisy data to train and verify a neural network model to reliably achieve a high-level of prediction accuracy.CIted as: Moosavi, S.R., Vaferi, B., Wood, D.A. Auto-detection interpretation model for horizontal oil wells using pressure transient responses. Advances in Geo-Energy Research, 2020, 4(3): 305-316, doi: 10.46690/ager.2020.03.08