The paper focuses on investigation of properties of two most widely used self-set sand binder systems APNB and FNB across the Globe, for making molds and cores in foundries to produce castings of different sizes involving wide range of metals and alloys, ferrous and nonferrous. This includes study of compression strength values of samples made out of molding sand at different binder addition level using new, mechanically reclaimed (MR) and thermally reclaimed (TR) sand. Strength values studied include dry strength (at room temperature) at specified intervals simulating different stages of mold handling, namely stripping and pre heating, followed by degraded strength after application of thinner based zircon wash by brush, subsequent lighting of, then checking strength both in warm (degraded strength) & cold (recovered strength) conditions. Throughout the cycle of mold movement from stripping to knock out, strength requirements can be divided into two broad classifications, one from stripping to closing (dry strength) and another from pouring to knock out (hot & retained strength). Although the process for checking of dry strength are well documented, no method using simple equipments for checking hot & retained strength are documented in literature. Attempts have been made in this paper to use some simple methods to standardize process for checking high strength properties using ordinary laboratory equipments. Temperature of 450°C has been chosen by trial & error method to study high temperature properties to get consistent & amplified values. Volume of gases generated for both binders in laboratory at 850°C have also been measured. Nature of gases including harmful BTEX and PAH generated on pyrolysis of FNB and APNB bonded sands are already documented in a publication [1]. This exercise has once again been repeated in same laboratory, AGH University, Poland with latest binder formulations in use in two foundries in India.

Speech and music signals are multifractal phenomena. The time displacement profile of speech and music signal show strikingly different scaling behaviour. However, a full complexity analysis of their frequency and amplitude has not been made so far. We propose a novel complex network based approach (Visibility Graph) to study the scaling behaviour of frequency wise amplitude variation of speech and music signals over time and then extract their PSVG (Power of Scale freeness of Visibility Graph). From this analysis it emerges that the scaling behaviour of amplitude-profile of music varies a lot from frequency to frequency whereas it’s almost consistent for the speech signal. Our left auditory cortical areas are proposed to be neurocognitively specialised in speech perception and right ones in music. Hence we can conclude that human brain might have adapted to the distinctly different scaling behaviour of speech and music signals and developed different decoding mechanisms, as if following the so called Fractal Darwinism. Using this method, we can capture all non-stationary aspects of the acoustic properties of the source signal to the deepest level, which has huge neurocognitive significance. Further, we propose a novel non-invasive application to detect neurological illness (here autism spectrum disorder, ASD), using the quantitative parameters deduced from the variation of scaling behaviour for speech and music.