Synthesis and Antimicrobial Evaluation of Some Novel Thiazole, Pyridone, Pyrazole, Chromene, Hydrazone Derivatives Bearing a Biologically Active Sulfonamide Moiety

This study aimed for the synthesis of new heterocyclic compounds incorporating sulfamoyl moiety suitable for use as antimicrobial agents via a versatile, readily accessible N-[4-(aminosulfonyl)phenyl]-2-cyanoacetamide (3). The 2-pyridone derivatives were obtained via reaction of cyanoacetamide with acetylacetone or arylidenes malononitrile. Cycloaddition reaction of cyanoacetamide with salicyaldehyde furnished chromene derivatives. Diazotization of 3 with the desired diazonium chloride gave the hydrazone derivatives 13a–e. Also, the reactivity of the hydrazone towards hydrazine hydrate to give Pyrazole derivatives was studied. In addition, treatment of 3 with elemental sulfur and phenyl isothiocyanate or malononitrile furnished thiazole and thiophene derivatives respectively. Reaction of 3 with phenyl isothiocyanate and KOH in DMF afforded the intermediate salt 17 which reacted in situ with 3-(2-bromoacetyl)-2H-chromen-2-one and methyl iodide afforded the thiazole and ketene N,S-acetal derivatives respectively. Finally, reaction of 3 with carbon disulfide and 1,3-dibromopropane afforded the N-[4-(aminosulfonyl) phenyl]-2-cyano-2-(1,3-dithian-2-ylidene)acetamide product 22. All newly synthesized compounds were elucidated by considering the data of both elemental and spectral analysis. The compounds were evaluated for both their in vitro antibacterial and antifungal activities and showed promising results

The Random Neural Network in Price Predictions

Part 5: Neural Network ModelingInternational audienceEverybody likes to make a good prediction, in particular, when some sort of personal investment is involved in terms of finance, energy or time. The difficulty is to make a prediction that optimises the reward obtained from the original contribution; this is even more important when investments are the core service offered by a business or pension fund generated by monthly contributions. The complexity of finance is that the human predictor may have other interests or bias than the human investor, the trust between predictor and investor will never be completely established as the investor will never know if the predictor has generated, intentionally or unintentionally, the optimum possible reward. This paper presents the Random Neural Network in recurrent configuration that makes predictions on time series data, specifically, prices. The biological model inspired by the brain structure and neural interconnections makes predictions entirely on previous data from the time series rather than predictions based on several uncorrelated inputs. The model is validated against the property, stock and Fintech market: 1) UK property prices, 2) stock markets indice prices, 3) cryptocurrency prices. Experimental results show that the proposed method makes accurate predictions on different investment portfolios

Tensile fracture strength of Brisbane tuff by static and cyclic loading tests

This research presents the results of laboratory experiments during the investigation of tensile strength-strain characteristics of Brisbane tuff disc specimens under static and diametral cyclic loading. Three different cyclic loading methods were used; namely, sinusoidal cyclic loading, type I and II increasing cyclic loading with various amplitude values. The first method applied the stress amplitude-cycle number (s-n) curve approach to the measurement of the indirect tensile strength (ITS) and fracture toughness (K ) values of rocks for the first time in the literature. The type I and II methods investigated the effect of increasing cyclic loading on the ITS and K of rocks. For Brisbane tuff, the reduction in ITS was found to be 30 % under sinusoidal loading, whereas type I and II increasing cyclic loading caused a maximum reduction in ITS of 36 %. The maximum reduction of the static K of 46 % was obtained for the highest amplitude type I cyclic loading tested. For sinusoidal cyclic loading, a maximum reduction of the static K of 30 % was obtained. A continuous irreversible accumulation of damage was observed in dynamic cyclic tests conducted at different amplitudes and mean stress levels. Scanning electron microscope images showed that fatigue damage in Brisbane tuff is strongly influenced by the failure of the matrix because of both inter-granular fracturing and trans-granular fracturing. The main characteristic was grain breakage under cyclic loading, which probably starts at points of contact between grains and is accompanied by the production of very small fragments, probably due to frictional sliding within the weak matrix