The concept of strong and weak virtual reality

We approach the virtual reality phenomenon by studying its relationship to set theory, and we investigate the case where this is done using the wellfoundedness property of sets. Our hypothesis is that non-wellfounded sets (hypersets) give rise to a different quality of virtual reality than do familiar wellfounded sets. We initially provide an alternative approach to virtual reality based on Sommerhoff's idea of first and second order self-awareness; both categories of self-awareness are considered as necessary conditions for consciousness in terms of higher cognitive functions. We then introduce a representation of first and second order self-awareness through sets, and assume that these sets, which we call events, originally form a collection of wellfounded sets. Strong virtual reality characterizes virtual reality environments which have the limited capacity to create only events associated with wellfounded sets. In contrast, the more general concept of weak virtual reality characterizes collections of virtual reality mediated events altogether forming an entirety larger than any collection of wellfounded sets. By giving reference to Aczel's hyperset theory we indicate that this definition is not empty, because hypersets encompass wellfounded sets already. Moreover, we argue that weak virtual reality could be realized in human history through continued progress in computer technology. Finally, we reformulate our characterization into a more general framework, and use Baltag's Structural Theory of Sets (STS) to show that within this general hyperset theory Sommerhoff's first and second order self-awareness as well as both concepts of virtual reality admit a consistent mathematical representation.Comment: 17 pages; several edits in v

Solving Multiple Objective Programming Problems Using Feed-Forward Artificial Neural Networks: The Interactive FFANN Procedure

In this paper, we propose a new interactive procedure for solving multiple objective programming problems. Based upon feed-forward artificial neural networks (FFANNs), the method is called the Interactive FFANN Procedure. In the procedure, the decision maker articulates preference information over representative samples from the nondominated set either by assigning preference "values" to the sample solutions or by making pairwise comparisons in a fashion similar to that in the Analytic Hierarchy Process. With this information, a FFANN is trained to represent the decision maker's preference structure. Then, using the FFANN, an optimization problem is solved to search for improved solutions. An example is given to illustrate the Interactive FFANN Procedure. Also, the procedure is compared computationally with the Tchebycheff Method (Steuer and Choo 1983). From the computational results, the Interactive FFANN Procedure produces good results and is robust with regard to the neural network architecture

Interactive Multiple Objective Programming Using Tchebycheff Programs and Artificial Neural Networks

A new interactive multiple objective programming procedure is developed that combines the strengths of the Interactive Weighted Tchebycheff Procedure (Steuer and Choo 1983) and the Interactive FFANN Procedure (Sun, Stam and Steuer 1993). In this new procedure, nondominated trial solutions are generated by solving Augmented Weighted Tchebycheff Programs (Steuer 1986), based on which the decision maker articulates his/her preference information by assigning "values" to these solutions or by making pairwise comparisons. The elicited preference information is used to train a feed-forward artificial neural network, which in turn is used to screen new trial solutions for presentation to decision maker in the next iteration. Computational results are reported, comparing the current procedure with the Interactive Weighted Tchebycheff Procedure and the Interactive FFANN Procedure. The results show that this new procedure yields good quality solutions

Time-Optimal Adaptation in Metabolic Network Models

Analysis of metabolic models using constraint-based optimization has emerged as an important computational technique to elucidate and eventually predict cellular metabolism and growth. In this work, we introduce time-optimal adaptation (TOA), a new constraint-based modeling approach that allows us to evaluate the fastest possible adaptation to a pre-defined cellular state while fulfilling a given set of dynamic and static constraints. TOA falls into the mathematical problem class of time-optimal control problems, and, in its general form, can be broadly applied and thereby extends most existing constraint-based modeling frameworks. Specifically, we introduce a general mathematical framework that captures many existing constraint-based methods and define TOA within this framework. We then exemplify TOA using a coarse-grained self-replicator model and demonstrate that TOA allows us to explain several well-known experimental phenomena that are difficult to explore using existing constraint-based analysis methods. We show that TOA predicts accumulation of storage compounds in constant environments, as well as overshoot uptake metabolism after periods of nutrient scarcity. TOA shows that organisms with internal temporal degrees of freedom, such as storage, can in most environments outperform organisms with a static intracellular composition. Furthermore, TOA reveals that organisms adapted to better growth conditions than present in the environment (“optimists”) typically outperform organisms adapted to poorer growth conditions (“pessimists”)

Time-Optimal Adaptation in Metabolic Network Models

Analysis of metabolic models using constraint-based optimization has emerged as an important computational technique to elucidate and eventually predict cellular metabolism and growth. In this work, we introduce time-optimal adaptation (TOA), a new constraint-based modeling approach that allows us to evaluate the fastest possible adaptation to a pre-defined cellular state while fulfilling a given set of dynamic and static constraints. TOA falls into the mathematical problem class of time-optimal control problems, and, in its general form, can be broadly applied and thereby extends most existing constraint-based modeling frameworks. Specifically, we introduce a general mathematical framework that captures many existing constraint-based methods and define TOA within this framework. We then exemplify TOA using a coarse-grained self-replicator model and demonstrate that TOA allows us to explain several well-known experimental phenomena that are difficult to explore using existing constraint-based analysis methods. We show that TOA predicts accumulation of storage compounds in constant environments, as well as overshoot uptake metabolism after periods of nutrient scarcity. TOA shows that organisms with internal temporal degrees of freedom, such as storage, can in most environments outperform organisms with a static intracellular composition. Furthermore, TOA reveals that organisms adapted to better growth conditions than present in the environment (“optimists”) typically outperform organisms adapted to poorer growth conditions (“pessimists”).Peer Reviewe

Reproducible, Fast and Adjustable Surface Roughening of Stainless Steel using Pulse Electrochemical Machining

AbstractPulse Electrochemical Machining (PECM) is known to produce finished surfaces with a typical roughness in the region of conventional machining methods like grinding or lapping. Furthermore, the process characteristics support the leveling of a rough anodic surface by using an either smoother, equally rough or even rougher cathode. This research focuses on an empirical investigation of the contrary approach, since for some applications surfaces with a well-defined roughness within small tolerances are needed. Examples are forms for injection molding, medical implants and friction pairs. In this contribution the copying accuracy to specifically produce and reproduce a localized as well as adjustable rough surface structure in steel is analyzed under different process conditions. The surface structure and roughness of the used PECM cathodes are initially produced by Electrical Discharge Machining (EDM) using copper as electrode. This study will show how surface roughnesses can accurately be produced with PECM in a range of typical conventional and non-conventional machining methods. Furthermore, the possibility of adding a surface texture by PECM is pointed out which will create a similar result as an EDM process but without the disadvantages of heat affected zone, tool wear and long machining time for fine finishes. The changes of the surface roughness during the process chain - producing the electrodes by turning, machining the PECM cathodes with EDM and finally machining the parts with PECM - are measured in all stages and correlated to the process conditions and influencing parameters. For all PECM experiments a commercially available PEM Center8000 with sodium nitrate as electrolyte and for all EDM experiments a FORM 20 with IonoPlus IM E-MH as dielectric was used

Global communication part 1: the use of apparel CAD technology

Trends needed for improved communication systems, through the development of future computer-aided design technology (CAD) applications, is a theme that has received attention due to its perceived benefits in improving global supply chain efficiencies. This article discusses the developments of both 2D and 3D computer-aided design capabilities, found within global fashion supply chain relationships and environments. Major characteristics identified within the data suggest that CAD/CAM technology appears to be improving; however, evidence also suggest a plateau effect, which is accrediting forced profits towards information technology manufactures, and arguably compromising the industry's competitive advantage. Nevertheless, 2D CAD increases communication speed; whereas 3D human interaction technology is seen to be evolving slowly and questionably with limited success. The article discusses the findings and also presents the issues regarding human interaction; technology education; and individual communication enhancements using technology processes. These are still prevalent topics for the future developments of global strategy and cultural communication amalgamation

Effects of hypothalamic knife cuts and experience on maternal behavior in the rat

Recent investigations suggest that the disruption of placentophagia, pup-directed maternal behavior, and nestbuilding seen after lesions of the medial preoptic area (MPO) or the lateral hypothalamus may be due to the interruption at different points of a single longitudinal neural system mediating these behaviors. To test this, we compared the effects of knife cuts on the lateral border of the MPO, and of the posterior medial forebrain bundle (MFB), with asymmetrical cuts combining a unilateral MPO cut with a contralateral MFB cut. We observed placentophagia, nestbuilding, and pup-directed maternal behaviors at, and after, parturition in both primiparous and biparous rats. In primiparae, MPO cuts (a) disrupted placentophagia, (b) delayed the onset of crouching and pup-licking, and (c) eliminated retrieval and nestbuilding. Asymmetrical cuts (a) disrupted placentophagia, and (b) delayed the onset of maternal behavior. In biparous rats, MPO cuts eliminated nestbuilding and retrieval. MFB cuts (a) disrupted placentophagia, and (b) eliminated nestbuilding. Asymmetrical cuts (a) delayed nestbuilding. These results suggest the involvement of a longitudinal neural system in the production of immediate pup-directed maternal behavior, placentophagia, and nestbuilding in parturient primiparae, but which is not critical for the eventual display of maternal behavior and nestbuilding in maternally naive rats, nor for the immediate onset of placentophagia and maternal behavior in maternally experienced rats

Urinary concentrations of GHB and its novel amino acid and carnitine conjugates following controlled GHB administration to humans

Gamma-hydroxybutyrate (GHB) remains a challenging clinical/forensic toxicology drug. Its rapid elimination to endogenous levels mainly causes this. Especially in drug-facilitated sexual assaults, sample collection often occurs later than the detection window for GHB. We aimed to investigate new GHB conjugates with amino acids (AA), fatty acids, and its organic acid metabolites for their suitability as ingestion/application markers in urine following controlled GHB administration to humans. We used LC–MS/MS for validated quantification of human urine samples collected within two randomized, double-blinded, placebo-controlled crossover studies (GHB 50 mg/kg, 79 participants) at approximately 4.5, 8, 11, and 28 h after intake. We found significant differences (placebo vs. GHB) for all but two analytes at 4.5 h. Eleven hours post GHB administration, GHB, GHB-AAs, 3,4-dihydroxybutyric acid, and glycolic acid still showed significantly higher concentrations; at 28 h only GHB-glycine. Three different discrimination strategies were evaluated: (a) GHB-glycine cut-off concentration (1 µg/mL), (b) metabolite ratios of GHB-glycine/GHB (2.5), and (c) elevation threshold between two urine samples (> 5). Sensitivities were 0.1, 0.3, or 0.5, respectively. Only GHB-glycine showed prolonged detection over GHB, mainly when compared to a second time- and subject-matched urine sample (strategy c)