The Proceedings of the Eighth International Conference on Creationism (2018)

actively and continuously track environmental changes, and 3) changes in an organism’s traits should occur in parallel with the rate and magnitude of environmental changes. Wehave termed this hypothesis ContinuousEnvironmental Tracking (CET). It is the foundational assumption of a new framework for understanding diversification and adaptation. Scientific activities including interpretations of findings take place within a structure of ideas and assumptions defining a field of study. The framework we offer promotes comparing data and observations (findings) of reported biological functions to those of human-engineered entities to search for: corresponding systems and their elements, mechanisms, engineering principles fundamental to operation, and assembly processes to assist in research. Our framework widens the bi-directional conduit between engineering and biology by aiding bioengineers in their job of biomimicry and aids biologists to predict where to search for elusive system elements or steps, guided by the assumption of functional purpose(s). Reinterpreting the findings of biological studies by an “engineering approach” or “design analysis” means that they are evaluated with this comparison of biological functions to those of human-engineered entities in mind. B. Expected features of CET biological mechanisms What are the elements of biological systems that should correspond to man-made tracking systems? Tracking systems are generally part of larger, robust, adaptive control systems. These follow the movement of a select “target” within a specified “field of view” and elicit response per a predetermined algorithm. These “surveillance systems” use one or more sensors, coupled to a computer system, that gather and interpret incoming data about uncertain environments. (Blackman and Popoli 1999). There are three irreducible elements common to all tracking systems: 1) sensors to detect pre-specified conditions; 2) condition- consequence logic mechanisms that process information by specifying if (+) condition then (+) consequential output response, and 3) output responses which adjust activities to effectively pursue a target (Blackman and Popoli 1999; Ioannou and Sun. 2012). (If navigation or interception at a precise location is desired, then a chronometer or circadian device tomeasures time is also an essential element.) If the CET hypothesis is correct, we would expect to find biological mechanisms with corresponding irreducible elements that are recognizable by the following characteristics: (1) Sensors. The element linking the system to its environment is the sensor. Fraden, a system design specialist, highlights the role of sensors in initiating data acquisition, “a sensor does not function by itself; it is always a part of a larger system that may incorporate many other detectors, signal conditioners, signal processors, memory devices, data recorders, and actuators…A sensor is always a part of some kind of a data acquisition system…Depending on the complexity of the system, the total number of sensors may vary from as little as one (a home thermostat) to many thousands (a space shuttle)” (Fraden 2010, p.5). Understanding three key characteristics of how sensors integrate into systems helps illuminate important details of the relationship between an entity and exposures. First, sensors are exquisitely designed to be selective by specifying the environmental conditions to which they will be sensitive and insensitive. Sensors should minimally disturb the condition being monitored so its “true value” remains. Second, a sensor must be ready to collect data by means of detecting a condition, often by “active surveillance.” Third, sensors are an integral part of the system. This relationship may be difficult to see since sensors are often remotely located. (2) Logic mechanisms. Sophisticated internal logic mechanisms are currently being designed as more than basic if-then types of on- off switches (or gates.) Engineers are patterning logic mechanisms in tracking systems after the nervous system in living organisms so that they function as artificial neural networks. Ioannou (2012) believes his approach to adaptive control systems “…will be of great interest to the neural and fuzzy logic audience who will benefit from the strong similarity that exists between adaptive systems, whose stability properties are well established, and neural networks, fuzzy logic systems where stability and convergence issues are yet to be resolved” (p. xiv). The logical programming may be extraordinarily complex and mathematically rigorous to process the array of incoming variables, especially when multiple sensors are tracking multiple moving targets (Oh et al. 2013). Advanced logical programming integrates data from multiple sensors with pre-programmed ranges to further reduce target- tracking uncertainties by filtering out useless data or “noise” and to make determinations on the validity of data prior to specifying an output response (Luo et al. 2002). (3) Output responses. The final step in tracking is to respond to target movements. Though the response is usually a necessary consequence when specific conditions are encountered, responses can range from a simple discreet on-off action, to a continuous range produced by an algorithm utilizing input variables. This is illustrated in the multiple uses for tracking eye movements which range from medical diagnostics, refractive surgery, human- computer interfaces, and commercial marketing (Gneo et al. 2012). Responses may be integral to a tracking system itself, such as a mechanism using stepping motors to keep a solar panel tracking the sun’s movement. Implications of this hypothesis help clarify biological adaptability Afundamental design constraint is that the capacities for a designed entity to both relate to—and adapt to—external conditions must be built entirely into an entity. In terms of external conditions, these are insufficient to cause changes to an internal system’s function. An engineer would identify conditions pertinent to performance and may specify some (amongst a myriad of conditions) as variables that are either present or not. The implication of the utilization of engineering principles and causation is reflected in the second half of our engineering-based, organism-focused characterization which keeps the operational spotlight on the organism rather than the environment. An engineering approach focuses on whole systems and not individual elements. Since the entire system ceases to function with the loss of any vital element, then, no single element is declared to be causal. Only verifiable elements are included—and no vital element is omitted—in causal chains. With this primarily descriptive approach, causal chains in organism will: 1) generally link genetic or epigenetic information through, 2) specific systems Guliuzza and Gaskill ◀ How organisms continuously track environmental changes ▶ 2018 ICC 161