We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substant...

Best Practice Recommendations for Designing and Implementing Experimental Vignette Methodology Studies

With much advancement in the field of nanotechnology, bioengineering, and synthetic biology over the past decade, microscales and nanoscales devices are becoming a reality. Yet the problem of engineering a reliable communication system between tiny devices is still an open problem. At the same time, despite the prevalence of radio communication, there are still areas where traditional electromagnetic waves find it difficult or expensive to reach. Points of interest in industry, cities, and medical applications often lie in embedded and entrenched areas, accessible only by ventricles at scales too small for conventional radio waves and microwaves, or they are located in such a way that directional high frequency systems are ineffective. Inspired by nature, one solution to these problems is molecular communication (MC), where chemical signals are used to transfer information. Although biologists have studied MC for decades, it has only been researched for roughly 10 year from a communication engineering lens. Significant number of papers have been published to date, but owing to the need for interdisciplinary work, much of the results are preliminary. In this survey, the recent advancements in the field of MC engineering are highlighted. First, the biological, chemical, and physical processes used by an MC system are discussed. This includes different components of the MC transmitter and receiver, as well as the propagation and transport mechanisms. Then, a comprehensive survey of some of the recent works on MC through a communication engineering lens is provided. The survey ends with a technology readiness analysis of MC and future research directions.

/pdf/a-comprehensive-survey-of-recent-advancements-in-molecular-2pjzig1xwb.pdf

A Comprehensive Survey of Recent Advancements in Molecular Communication

Chemotactic bacteria are guided towards the source of a nutrient by local concentration gradients. That works on the microscopic scale, but at larger scales such local cues are unreliable pointers — for example, wind or water currents may disperse odours sought by foraging animals. Using statistical techniques, Vergassola et al. have developed a general search algorithm for movement strategies based on the detection of sporadic cues and partial information. The strategy, termed 'infotaxis' as it maximizes the expected rate of information gain, could find application in the design of 'sniffer' robots. A computational model of odour plume propagation and experimental data are used to devise a general search algorithm for movement strategies in chemotaxis, based on sporadic cues and partial information. The strategy is termed 'infotaxis' as it locally maximizes the expected rate of information gain. Chemotactic bacteria rely on local concentration gradients to guide them towards the source of a nutrient1. Such local cues pointing towards the location of the source are not always available at macroscopic scales because mixing in a flowing medium breaks up regions of high concentration into random and disconnected patches. Thus, animals sensing odours in air or water detect them only intermittently as patches sweep by on the wind or currents2,3,4,5,6. A macroscopic searcher must devise a strategy of movement based on sporadic cues and partial information. Here we propose a search algorithm, which we call ‘infotaxis’, designed to work under such conditions. Any search process can be thought of as acquisition of information on source location; for infotaxis, information plays a role similar to concentration in chemotaxis. The infotaxis strategy locally maximizes the expected rate of information gain. We demonstrate its efficiency using a computational model of odour plume propagation and experimental data on mixing flows7. Infotactic trajectories feature ‘zigzagging’ and ‘casting’ paths similar to those observed in the flight of moths8. The proposed search algorithm is relevant to the design of olfactory robots9,10,11, but the general idea of infotaxis can be applied more broadly in the context of searching with sparse information.

"Infotaxis" as a strategy for searching without gradients

A comprehensive review is presented on the development and state of the art of colorimetric and fluorometric sensor arrays. Optical arrays based on chemoresponsive colorants (dyes and nanoporous pigments) probe the chemical reactivity of analytes, rather than their physical properties. This provides a high dimensionality to chemical sensing that permits high sensitivity (often down to ppb levels), impressive discrimination among very similar analytes and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, both in the gas and liquid phases.

https://zenodo.org/record/895426/files/article.pdf

Optical sensor arrays for chemical sensing: the optoelectronic nose

A comprehensive review on the development and state of the art of colorimetric and fluorometric sensor arrays is presented Chemical sensing aims to detect subtle changes in the chemical environment by transforming relevant chemical or physical properties of molecular or ionic species (ie, analytes) into an analytically useful output Optical arrays based on chemoresponsive colorants (dyes and nanoporous pigments) probe the chemical reactivity of analytes, rather than their physical properties (eg, mass) The chemical specificity of the olfactory system does not come from specific receptors for specific analytes (eg, the traditional lock-and-key model of substrate-enzyme interactions), but rather olfaction makes use of pattern recognition of the combined response of several hundred olfactory receptors In a similar fashion, arrays of chemoresponsive colorants provide high-dimensional data from the color or fluorescence changes of the dyes in these arrays as they are exposed to analytes This provides chemical sensing with high sensitivity (often down to parts per billion levels), impressive discrimination among very similar analytes, and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, in both the gas and liquid phases Design of both sensor arrays and instrumentation for their analysis are discussed In addition, the various chemometric and statistical analyses of high-dimensional data (including hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA), support vector machines (SVMs), and artificial neural networks (ANNs)) are presented and critiqued in reference to their use in chemical sensing A variety of applications are also discussed, including personal dosimetry of toxic industrial chemical, detection of explosives or accelerants, quality control of foods and beverages, biosensing intracellularly, identification of bacteria and fungi, and detection of cancer and disease biomarkers

The Optoelectronic Nose: Colorimetric and Fluorometric Sensor Arrays.

A new device for determining the direction of a gas source is proposed. Peltier elements are used to transfer heat from the center of the device to its left and right sides. Ascending air currents generated from the warmed sides of the device bring a gaseous chemical substance trailing along the floor toward the right and left gas sensors. A descending air current is also generated from the colder central part of the device. This air current works as an air curtain and expands the sensor response difference. Experimental results are presented to show the soundness of the device design.

http://ieeexplore.ieee.org/iel5/6381733/6411021/06411401.pdf

Device for determining gas source direction that uses peltier elements to collect gas samples

We do not know of any modern cities free from air pollution. In Tokyo, the levels of nitrogen oxides, photochemical oxidants, and particulate matter often exceed the environmental quality standards. However, the cost and size of the chemical analyzers have limited the number of monitoring stations and, thus, the spatial resolution of the measured pollutant distributions. The authors have been proposing a gas distribution analyzing system (GASDAS). The use of gas sensors enables compact and inexpensive sensing systems, and leads to a significant increase in the density of monitoring sites. Various network technologies can be used to form a sensing network for efficient data collection. As a first step in the development of GASDAS, a measurement system for nitrogen dioxide and ozone has been developed using electrochemical and semiconductor gas sensors. Encouraging results have been obtained from both types of sensors, and the major interference gas to be addressed in future work has turned out to be nitrogen monoxide. A monitoring system for particulate matter has also been developed. A photosensor is used to measure the accumulation of particulate matter on an air filter. The experimental results have shown the potential of this simple method.

Compact atmospheric environmental monitoring system using gas sensors and network technology

In outdoor environments, fluctuating airflow and gas distribution make gas source localization (GSL) tasks difficult. In our research, we use neural networks (NNs) to overcome these difficulties by applying long short-term memory deep neural networks (LSTM-DNNs) to time series data taken from a gas sensor array and anemometer to estimate the position of a gas source. In this paper, we present NNs for GSL with the ability to use various length input data and estimate a gas source location each time-step. In doing so, we were able to estimate the location of a gas source within 40 time-steps (20 s) and achieved (using 300 time-steps) an estimation accuracy of 95%.

Application of Sequence Input and Output Long Short-Term Memory Neural Networks for Autonomous Gas Source Localization in an Outdoor Environment

We compared two measures of visually induced body sway—head motion and centre of pressure (CoP)—that were simultaneously measured while observing optic flow on a head-mounted display (HMD). Head motion can be conveniently tracked with HMDs, but may have some features different from those of conventional CoP measurements, because of the complex joint structures of the human body. In this analysis, the responses were very similar (except for response gain), and we did not find any significant differences in time or frequency domains. Our results support the use of head motion as a potential predictor of variability in body sway, at least in studies of visually guided postural control.

Comparing measurements of head motion and centre of pressure for body sway induced by optic flow on a head-mounted display

Two kinds of sensor systems for detecting gas trail (so-called plume) are discussed. One is the mobile robot with several kinds of sensors which can track the gas plume to search for a gas source. The other is the sensor network which can reveal the spatial and temporal behaviors of air-pollutant plumes in detail. The sensor network can also perform an automatic calibration to achieve a maintenance-free operation.

Hiroshi Ishida

Papers

Device for determining gas source direction that uses peltier elements to collect gas samples

Compact atmospheric environmental monitoring system using gas sensors and network technology

Application of Sequence Input and Output Long Short-Term Memory Neural Networks for Autonomous Gas Source Localization in an Outdoor Environment

Comparing measurements of head motion and centre of pressure for body sway induced by optic flow on a head-mounted display

Sensor Systems for Detecting Gas Plumes-Robots and Sensor Network