Biological Systems from an Engineer’s Point of View

Mathematical modeling of the processes that pattern embryonic development (often called biological pattern formation) has a long and rich history [1,2]. These models proposed sets of hypothetical interactions, which, upon analysis, were shown to be capable of generating patterns reminiscent of those seen in the biological world, such as stripes, spots, or graded properties. Pattern formation models typically demonstrated the sufficiency of given classes of mechanisms to create patterns that mimicked a particular biological pattern or interaction. In the best cases, the models were able to make testable predictions [3], permitting them to be experimentally challenged, to be revised, and to stimulate yet more experimental tests (see review in [4]). In many other cases, however, the impact of the modeling efforts was mitigated by limitations in computer power and biochemical data. In addition, perhaps the most limiting factor was the mindset of many modelers, using Occam’s razor arguments to make the proposed models as simple as possible, which often generated intriguing patterns, but those patterns lacked the robustness exhibited by the biological system. In hindsight, one could argue that a greater attention to engineering principles would have focused attention on these shortcomings, including potential failure modes, and would have led to more complex, but more robust, models. Thus, despite a few successful cases in which modeling and experimentation worked in concert, modeling fell out of vogue as a means to motivate decisive test experiments. The recent explosion of molecular genetic, genomic, and proteomic data—as well as of quantitative imaging studies of biological tissues—has changed matters dramatically, replacing a previous dearth of molecular details with a wealth of data that are difficult to fully comprehend. This flood of new data has been accompanied by a new influx of physical scientists into biology, including engineers, physicists, and applied mathematicians [5–7]. These individuals bring with them the mindset, methodologies, and mathematical toolboxes common to their own fields, which are proving to be appropriate for analysis of biological systems. However, due to inherent complexity, biological systems seem to be like nothing previously encountered in the physical sciences. Thus, biological systems offer cutting edge problems for most scientific and engineering-related disciplines. It is therefore no wonder that there might seem to be a “bandwagon” of new biology-related research programs in departments that have traditionally focused on nonliving systems. Modeling biological interactions as dynamical systems (i.e., systems of variables changing in time) allows investigation of systems-level topics such as the robustness of patterning mechanisms, the role of feedback, and the self-regulation of size. The use of tools from engineering and applied mathematics, such as sensitivity analysis and control theory, is becoming more commonplace in biology. In addition to giving biologists some new terminology for describing their systems, such analyses are extremely useful in pointing to missing data and in testing the validity of a proposed mechanism. A paper in this issue of PLoS Biology clearly and honestly applies analytical tools to the authors’ research and obtains insights that would have been difficult if not impossible by other means [8]

Multispectral scanner data processing over Sam Houston National Forest

The Edit 9 forest scene, a computer processing technique, and its capability to map timber types in the Sam Houston National Forest, are evaluated. Special efforts were made to evaluate existing computer processing techniques in mapping timber types using ERTS-1 and aircraft data, and to provide an opportunity to open up new research and development areas in forestry data

Light Elements and Cosmic Rays in the Early Galaxy

We derive constraints on the cosmic rays responsible for the Be and part of the B observed in stars formed in the early Galaxy: the cosmic rays cannot be accelerated from the ISM; their energy spectrum must be relatively hard (the bulk of the nuclear reactions should occur at $>$30 MeV/nucl); and only 10$^{49}$ erg/SNII in high metallicity, accelerated particle kinetic energy could suffice to produce the Be and B. The reverse SNII shock could accelerate the particles.Comment: 5 pages LATEX using paspconf.sty file with one embedded eps figure using psfig. In press, Proc. Goddard High Resolution Spectrograph Symposium, PASP, 199

Alabama's Senate runoff election mirrors the national struggle for the heart and soul of the Republican Party

Republican voters will go to the polls on September 26th to select the state's US Senator to replace Jeff Sessions, who President Trump elevated to the position of US Attorney General. Andrée E. Reeves gives an overview of the runoff race, which pits former state Supreme Court Justice Roy Moore against former Attorney General (and now incumbent US Senator) Luther ..

Long read: why the Alabama Senate race is now everyone's problem.

On November 9th, the Washington Post reported that allegations of past sexual misconduct had been levelled against former Alabama Chief Justice Roy Moore, who had been widely tipped to win the state's election for the US Senate on December 12th. Andrée Reeves writes that many in the GOP establishment have condemned or distanced themselves from the already controversial Moore, who ..

Charge exchange contribution to the decay of the ring current, measured by energetic neutral atoms (ENAs)

In this paper we calculate the contribution of charge exchange to the decay of the ring current. Past works have suggested that charge exchange of ring current protons is primarily responsible for the decay of the ring current during the late recovery phase, but there is still much debate about the fast decay of the early recovery phase. We use energetic neutral atom (ENA) measurements from Polar to calculate the total ENA energy escape. To get the total ENA escape we apply a forward modeling technique, and to estimate the total ring current energy escape we use the Dessler-Parker-Sckopke relationship. We find that during the late recovery phase of the March 10, 1998 storm ENAs with energies greater than 17.5 keV can account for 75% of the estimated energy loss from the ring current. During the fast recovery the measured ENAs can only account for a small portion of the total energy loss. We also find that the lifetime of the trapped ions is significantly shorter during the fast recovery phase than during the late recovery phase, suggesting that different processes are operating during the two phases