A History of Audio Effects

Audio effects are an essential tool that the field of music production relies upon. The ability to intentionally manipulate and modify a piece of sound has opened up considerable opportunities for music making. The evolution of technology has often driven new audio tools and effects, from early architectural acoustics through electromechanical and electronic devices to the digitisation of music production studios. Throughout time, music has constantly borrowed ideas and technological advancements from all other fields and contributed back to the innovative technology. This is defined as transsectorial innovation and fundamentally underpins the technological developments of audio effects. The development and evolution of audio effect technology is discussed, highlighting major technical breakthroughs and the impact of available audio effects

Upper Devonian microvertebrates from the Canning Basin, Western Australia

A diverse microvertebrate fauna is described from the Virgin Hills and Napier formations, Bugle Gap Limestone Canning Basin, Western Australia. Measured sections at horse Spring and Casey Falls (Virgin Hills Formation) and South Oscar Range (Napier Formation) comprise proximal to distal slope carbonates ranging in age from the Late Devonian Frasnian to middle Famennian. A total of 18 chondrichthyan taxa are identified based on teeth, including the first record of Thrinacodus tranquillus, Cladoides wildungensis, Protacrodus serra and Lissodus lusavorichi from the Canning Basin. A new species, Diademodus dominicus sp. nov. is also described and provided the first record of this genus outside of Laurussia. In addition, the upper range of Australolepis seddoni has been extended to Late Devonian conodont Zone 11, making it the youngest known occurrence for this species. The Virgin Hills and Napier formations microvertebrate faunas show close affinities to faunas recovered from other areas of Gondwana, including eastern Australia, Iran, Morocco and South China, which is consistent with known conodont and trilobite faunas of the same age

Immunization for complex network based on the effective degree of vertex

The basic idea of many effective immunization strategies is first to rank the importance of vertices according to the degrees of vertices and then remove the vertices from highest importance to lowest until the network becomes disconnected. Here we define the effective degrees of vertex, i.e., the number of its connections linking to un-immunized nodes in current network during the immunization procedure, to rank the importance of vertex, and modify these strategies by using the effective degrees of vertices. Simulations on both the scale-free network models with various degree correlations and two real networks have revealed that the immunization strategies based on the effective degrees are often more effective than those based on the degrees in the initial network.Comment: 16 pages, 5 figure

On the tree-transformation power of XSLT

XSLT is a standard rule-based programming language for expressing transformations of XML data. The language is currently in transition from version 1.0 to 2.0. In order to understand the computational consequences of this transition, we restrict XSLT to its pure tree-transformation capabilities. Under this focus, we observe that XSLT~1.0 was not yet a computationally complete tree-transformation language: every 1.0 program can be implemented in exponential time. A crucial new feature of version~2.0, however, which allows nodesets over temporary trees, yields completeness. We provide a formal operational semantics for XSLT programs, and establish confluence for this semantics

Coarse-Graining and Self-Dissimilarity of Complex Networks

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units (CGU) as connectivity patterns which can serve as the nodes of a coarse-grained network, and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then, the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit-module made of multiple gates. We apply our approach also to a mammalian protein-signaling network, to find a simplified coarse-grained network with three main signaling channels that correspond to cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are 'self-dissimilar', with different network motifs found at each level. The present approach can be used to simplify a wide variety of directed and nondirected, natural and designed networks.Comment: 11 pages, 11 figure

Cell fueling and metabolic energy conservation in synthetic cells

We aim for a blue print for synthesizing complex subcellular systems from molecular components and ultimately for constructing life. Without comprehensive instructions and design principles we rely on simple reaction routes to operate the essential functions of life. The first forms of synthetic life will not make every building block for polymers de novo via complex pathways, rather they will be fed with amino acids, fatty acids and nucleotides. Controlled energy supply is crucial for any synthetic cell, no matter how complex. Here, we describe the simplest pathways for efficient generation of ATP and electrochemical ion gradients. We estimated the demand for ATP by polymer synthesis and maintenance processes in small cell-like systems, and we describe circuits to control the needs for ATP. We also present fluorescence-based sensors for pH, ionic strength, excluded volume, ATP/ADP, and viscosity, which allow monitoring and tuning of the major physicochemical conditions inside cells

Physical Optics Solution for the Scattering of a Partially-coherent Wave from a Statistically Rough Material Surface

The scattering of a partially-coherent wave from a statistically rough material surface is investigated via derivation of the scattered field cross-spectral density function. Two forms of the cross-spectral density are derived using the physical optics approximation. The first is applicable to smooth-to-moderately rough surfaces and is a complicated expression of source and surface parameters. Physical insight is gleaned from its analytical form and presented in this work. The second form of the cross-spectral density function is applicable to very rough surfaces and is remarkably physical. Its form is discussed at length and closed-form expressions are derived for the angular spectral degree of coherence and spectral density radii. Furthermore, it is found that, under certain circumstances, the cross-spectral density function maintains a Gaussian Schell-model form. This is consistent with published results applicable only in the paraxial regime. Lastly, the closed-form cross-spectral density functions derived here are rigorously validated with scatterometer measurements and full-wave electromagnetic and physical optics simulations. Good agreement is noted between the analytical predictions and the measured and simulated results. © 2013 Optical Society of Americ

NFPA Fluid Powered Vehicle Challenge 2023

This report includes the design process undergone by Team Shifty in designing a vehicle for the NFPA’s Fluid Powered Vehicle challenge. The report covers the background of the competition, research done by the team, engineering specifications for the design, preliminary and final designs, the manufacturing plan and process, project management details, and several recommendations for future teams participating in the challenge. The National Fluid Power Association, NFPA, is a trade association with the goal of connecting fluid power companies and advancing fluid power. With the goal of advancement in mind, NFPA hosts an annual Fluid Powered Vehicle Challenge (FPVC). Since before the NFPA took over this challenge, Cal Poly has produced a team to compete. Team Shifty completed research into past Cal Poly teams as well as other competing university teams to define the engineering specifications for the new vehicle and decide the design directions. The final design includes a new frame to address issues with the last teams frame, a new hydraulic circuit design and selection of new components to improve the circuits performance in the FPVC events and reduce losses, and the addition of gear shifting to the vehicle. With respect to hydraulics, a new manifold was sourced to accommodate the simplified fluid circuit, along with a larger motor to allow the vehicle to operate at higher torque. The prior team’s pneumatic system was completely replaced by a pneumatic front gear shifting system. The electronics implemented was the same system as the previous year, including an STM microcontroller, Nextion touch screen display, and Hydraforce valve operator with only two solenoid valves. Working together, these components allowed the rider to toggle between three unique drive modes, including: direct, regen, and sprint. To produce a functional vehicle, research and planning was put into manufacturing and assembly processes as detailed in the manufacturing plan. The final product failed to perform as proposed in Team Shifty’s Scope of Work, as the vehicle’s rear chain consistently fell off during operation at the competition. This resulted in the vehicle not placing during a few of the challenges, including the Sprint and Endurance races. The cause of this failure was a function of the frame flexing under dynamic loading due to insufficient torsional stiffness, as well as the rear chain being too small to handle the large output torque of the upsized rear motor

Examining the Validity of Using a Gaussian Schell-Model Source To Model the Scattering of A Fully Coherent Gaussian Beam From A Rough Impedance Surface

Military applications that use adaptive optics (AO) often require a point source beacon at the target to measure and correct for wavefront aberrations introduced by atmospheric turbulence. However, turbulence prevents the formation of such a point beacon. The extended beacons that are created instead have finite spatial extents and exhibit varying degrees of spatial coherence. Modeling these extended beacons using a Gaussian Schell-model (GSM) form for the autocorrelation function would be a convenient approach due to the analytical tractability of Gaussian functions. We examine the validity of using such a model by evaluating the field scattered from a rough impedance surface using a full-wave computational technique called the method of moments (MoM). The MoM improves the fidelity of the analysis since it captures all the physics of the laser-target interaction, such as masking, shadowing, multiple reflections, etc. Two rough-surface targets with different roughness statistics are analyzed. The simulation results are verified with experimental bidirectional reflectance distribution function measurements. It is seen that for rough surfaces, in general, the scattered-field autocorrelation function is not of a GSM form. However, under certain conditions, modeling an extended beacon as a GSM source is legitimate. This analysis will aid in understanding the behavior of extended beacons and how they affect the overall performance of an AO system

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models