Transport in Mazes; Simple Geometric Representations to Guide the Design of Engineered Systems

2022 ◽  
pp. 117416
Author(s):  
Alex Guo ◽  
William C. Marshall ◽  
Corey C. Woodcock ◽  
Joel L. Plawsky
2000 ◽  
Vol 42 (12) ◽  
pp. 49-60 ◽  
Author(s):  
P.L. McCarty

Of recent concern is the removal of toxic compounds in wastewaters, soils, and groundwater to concentrations in the low microgram per litre level or less. Threshold limits to bioremediation exist and must be considered in biological treatment schemes to achieve such limits. These limits may be related to reaction kinetics or thermodynamics. Techniques for removing compounds below threshold levels exist that rely on appropriate approaches such as plug flow treatment. Novel biological methods exist for removal of refractory contaminants to low levels. Examples are provided for removal of trace levels of chlorinated solvents, such as tetrachloroethene (PCE) and trichloroethene (TCE), that employ dehalorespiration under anaerobic conditions or cometabolism under aerobic conditions. These approaches are currently being used in engineered systems or through natural attenuation for remediation of soils and groundwater. Successful results offer insights for similar removals of trace chemicals in both aerobic and anaerobic biological systems for treatment of wastewaters and sanitary landfills.


Author(s):  
Joel Z. Leibo ◽  
Tomaso Poggio

This chapter provides an overview of biological perceptual systems and their underlying computational principles focusing on the sensory sheets of the retina and cochlea and exploring how complex feature detection emerges by combining simple feature detectors in a hierarchical fashion. We also explore how the microcircuits of the neocortex implement such schemes pointing out similarities to progress in the field of machine vision driven deep learning algorithms. We see signs that engineered systems are catching up with the brain. For example, vision-based pedestrian detection systems are now accurate enough to be installed as safety devices in (for now) human-driven vehicles and the speech recognition systems embedded in smartphones have become increasingly impressive. While not being entirely biologically based, we note that computational neuroscience, as described in this chapter, makes up a considerable portion of such systems’ intellectual pedigree.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 87775-87799 ◽  
Author(s):  
S. Neda Naghshbandi ◽  
Liz Varga ◽  
Alan Purvis ◽  
Richard Mcwilliam ◽  
Edmondo Minisci ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3420
Author(s):  
Marc Jofre ◽  
Lluís Jofre ◽  
Luis Jofre-Roca

The investigation of the electromagnetic properties of biological particles in microfluidic platforms may enable microwave wireless monitoring and interaction with the functional activity of microorganisms. Of high relevance are the action and membrane potentials as they are some of the most important parameters of living cells. In particular, the complex mechanisms of a cell’s action potential are comparable to the dynamics of bacterial membranes, and consequently focusing on the latter provides a simplified framework for advancing the current techniques and knowledge of general bacterial dynamics. In this work, we provide a theoretical analysis and experimental results on the microwave detection of microorganisms within a microfluidic-based platform for sensing the membrane potential of bacteria. The results further advance the state of microwave bacteria sensing and microfluidic control and their implications for measuring and interacting with cells and their membrane potentials, which is of great importance for developing new biotechnologically engineered systems and solutions.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
N. Birbilis ◽  
S. Choudhary ◽  
J. R. Scully ◽  
M. L. Taheri

AbstractMetallic alloys are critical to essentially all advanced technologies and engineered systems. The well-documented impact of corrosion (and oxidation) of alloys, remains a significant industrial and economic challenge, year on year. Recent activity in the field of metallurgy has revealed a class of metallic alloys, termed multi principal element alloys (MPEAs) that present unique physical properties. Such MPEAs have in many instances also demonstrated a high resistance to corrosion – which may permit the broader use of MPEAs as corrosion resistant alloys (CRAs) in harsh environments. Herein, the progress in MPEA research to date, along with prospects and challenges, are concisely reviewed—with potential future lines of research elaborated.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haron M. Abdel-Raziq ◽  
Daniel M. Palmer ◽  
Phoebe A. Koenig ◽  
Alyosha C. Molnar ◽  
Kirstin H. Petersen

AbstractIn digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.


2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Nafaâ Jabeur ◽  
Nabil Sahli ◽  
Sherali Zeadally

Wireless sensor networks (WSNs) are key components in the emergent cyber physical systems (CPSs). They may include hundreds of spatially distributed sensors which interact to solve complex tasks going beyond their individual capabilities. Due to the limited capabilities of sensors, sensor actions cannot meet CPS requirements while controlling and coordinating the operations of physical and engineered systems. To overcome these constraints, we explore the ecosystem metaphor for WSNs with the aim of taking advantage of the efficient adaptation behavior and communication mechanisms of living organisms. By mapping these organisms onto sensors and ecosystems onto WSNs, we highlight shortcomings that prevent WSNs from delivering the capabilities of ecosystems at several levels, including structure, topology, goals, communications, and functions. We then propose an agent-based architecture that migrates complex processing tasks outside the physical sensor network while incorporating missing characteristics of autonomy, intelligence, and context awareness to the WSN. Unlike existing works, we use software agents to map WSNs to natural ecosystems and enhance WSN capabilities to take advantage of bioinspired algorithms. We extend our architecture and propose a new intelligent CPS framework where several control levels are embedded in the physical system, thereby allowing agents to support WSNs technologies in enabling CPSs.


Sign in / Sign up

Export Citation Format

Share Document