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Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

In streams, phototrophic biofilms are considered to be a good‐quality resource for consumers and are essential to support secondary production. However, with the increasing occurrence of flow intermittency as a consequence of global climate change, limited information exists regarding the impact of drying and rewetting events on biofilm nutritional quality indicators and their consequences for consumers. This study aims at understanding how river intermittency affects the nutritional quality of phototrophic biofilms. Specifically, we examine the effects of drying and rewetting events on their capacity to support secondary production.Our hypothesis was that the capacity of biofilms to support secondary production relies on their nutritional quality: biofilms characterised by higher contents of long‐chain fatty acids, nitrogen and phosphorus are expected to provide a better‐quality resource for consumers. We also hypothesised that the nutritional quality of biofilms undergoes changes over time during drying events, and that these changes are influenced by their initial algal composition. This is because the algal composition within biofilms may shift in response to drying events, subsequently impacting the nutritional quality of the biofilms.We grew four phototrophic biofilms in flowing water, each with a different nutritional quality, and then exposed them to a short (3 days) or a long dry period (14 days). Biofilms were sampled 3 days and 18 days after rewetting (post‐disturbance and post‐recovery) to assess alterations in nutritional indicators relative to their pre‐disturbance state through pigment, fatty acid and stoichiometric analyses. We fed these biofilms to Gammarids (Gammarus fossarum) for 29 days and measured individual growth, feeding rate and locomotor activity. We also calculated a secondary production index to assess the biofilms' capacity to support higher trophic levels.Our findings revealed that the nutritional quality of biofilms was significantly reduced during the post‐disturbance phase. The duration of the dry period had minimal effect on this decline. Subsequently, during the recovery phase, nutritional quality indicators improved for biofilms initially dominated by cyanobacteria, while they either remained unchanged or decreased for biofilms initially dominated by diatoms, in comparison to the pre‐disturbance state. As a result, biofilms that initially exhibited a high nutritional quality were disrupted by the dry period, depending on the duration. However, the overall effects of dry period on gammarid's response and on secondary production were less pronounced, which is likely to have resulted from changes in the quantity of available resources.Our study demonstrates that a disturbance can modify the expected and effective qualities of biofilms. It highlights that biochemical parameters cannot reliably predict biofilm capacity to support secondary production. Biofilm history of disturbance, among other parameters, must be taken into account. [ABSTRACT FROM AUTHOR]

The inspection and maintenance of large-scale industrial structures are major challenges that require time-efficient and reliable solutions to ensure the healthy condition of structures during operation. Autonomous robots may provide a promising solution for this purpose. In particular, they could lead to faster and more reliable inspection and maintenance without direct intervention from human operators. In this paper, we present a custom magnetic crawler system, and sensor suit and sensing modalities to enable such robotic operation. We first describe a localization framework based on a mesh created from a point cloud coupled with Inertial Measurement Unit (IMU) and Ultra-Wide Band (UWB) readings. Next, we introduce a mapping framework that relies on a 3D laser, and explicitly state how autonomous navigation and obstacle avoidance can be developed. Lastly, we present how ultrasonic guided waves (UGWs) are integrated into the system to provide accurate robot localization and structural feature mapping by relying on acoustic reflections in combination with the other systems. It is envisioned that long-range inspection capabilities that are not yet available in current industrial mobile platforms could emerge from the designed robotic system. [ABSTRACT FROM AUTHOR]

Background: Mobile genetic elements (MGEs) are widely involved in the dissemination of antibiotic resistance genes and some of them, such as the integrative and conjugative element SXT, are even induced by specific antibiotics at sub-lethal concentrations.Objectives: This work explores collateral effects of a broad range of antibiotics on the mobility of the SXTMO10 element using a specifically designed high-throughput screening test.Methods: Twenty-five promoters involved in the mobility of SXT and six artificial constitutive promoters were transcriptionally fused to luxCDABE bioluminescent genes and introduced into Escherichia coli strains with or without SXT to build whole-cell biosensors for a large-scale screening involving 48 antibiotics. A bioluminescent assay implementing a classical agar diffusion approach was coupled to an automated data processing pipeline developed to extract and analyse luminescence data from over 2000 antibiotic/biosensor combination profiles.Results: In addition to quinolones previously reported as inducing the expression of SXT mobility genes, we found that specific antibiotics belonging to other classes, such as imipenem and azithromycin, also behave as inducers. The use of a control set of constitutive biosensors also revealed an unexpected intricate relationship between cell respiration and light production that allowed the identification of antibiotics interfering with the respiration process.Conclusions: The effect of antibiotics goes beyond the interaction with their primary cell targets and may lead to adverse effects such as triggering the dissemination of resistance by MGEs, sometimes in unpredictable ways. Identifying such MGE-triggering antibiotics is of prime importance for better controlling collateral effects during therapy. [ABSTRACT FROM AUTHOR]

Autonomous robotic weeding systems in precision farming have demonstrated their full potential to alleviate the current dependency on agrochemicals such as herbicides and pesticides, thus reducing environmental pollution and improving sustainability. However, most previous works require fast and constant‐time weed detection systems to achieve real‐time treatment, which forecloses the implementation of more capable but time‐consuming algorithms, for example, learning‐based methods. In this paper, a nonoverlapping multicamera system is applied to provide flexibility for the weed control system in dealing with the indeterminate classification delays. The design, implementation, and testing of our proposed modular weed control unit with mechanical and chemical weeding tools are presented. A framework that performs naive Bayes filtering, 3D direct intra‐ and inter‐camera visual tracking, and predictive control, while integrating state‐of‐the‐art crop/weed detection algorithms, is developed to guide the tools to achieve high‐precision weed removal. The experimental results show that our proposed fully operational weed control system is capable of performing selective mechanical as well as chemical in‐row weeding with indeterminate detection delays in different terrain conditions and crop growth stages. [ABSTRACT FROM AUTHOR]

This article presents a new framework to help transform visual surveys of a natural environment into time-lapses. As data association across year-long variation in appearance continues to represent a formidable challenge, we present success with a map-centric approach, which builds on 3D vision for visual data association. We use a foundation of map point priors and geometric constraints within a dense correspondence image alignment optimization to align images and acquire loop closures between surveys. This framework produces many loop closures between sessions. Outlier loop closures are filtered in the frontend and in the backend to improve robustness. From the result map, the Reprojection Flow algorithm is applied to create time-lapses. The evaluation of our framework on the Symphony Lake Dataset, which has considerable variation in appearance, led to year-long time-lapses of many different scenes. In comparison with another approach based on using iterative closest point (ICP) plus a homography, our framework produced more and better-quality alignments. With many scenes of the 1.3 km environment consistently aligning well in random image pairs, we next produced 100 time-lapses across 37 surveys captured in a year. Approximately one-third had at least 20 (out of usually 33) well-aligned images, which spanned all four seasons. With promising results, we evaluated the pose error of misaligned image pairs and found that improving map consistency could lead to even better results. [ABSTRACT FROM AUTHOR]

This paper describes Symphony Lake Dataset, 121 visual surveys of an approximately 1.3 km lake shore in Metz, France. Different from roadway datasets, it adds breadth to the data space at a time when larger and more diverse datasets are desired. Over five million images from an unmanned surface vehicle captured the natural environment as it evolved over three years. Variation in appearance across weeks, seasons, and years is significant. Success on Symphony Lake Dataset could demonstrate advancements in perception, simultaneous localization and mapping, and environment monitoring. [ABSTRACT FROM AUTHOR]

This paper presents a survey registration framework to assist in the recurrent inspection of a natural environment. Our framework coarsely aligns surveys at the image-level using visual simultaneous localization and mapping (SLAM), and it registers images at the pixel-level using SIFT Flow, which enables rapid manual inspection. The variation in appearance of natural environments makes data association a primary challenge of this work. We discuss this and other challenges, including 1) alternative approaches for coarsely aligning surveys of a natural environment, 2) how to select which images to compare between two surveys, and 3) strategies to boost image registration accuracy. We evaluate each stage of our approach, emphasizing alignment accuracy and stability with respect to large seasonal variations. Our domain is lakeshore monitoring, in which an autonomous surface vessel surveyed a 1-km lakeshore 33 times in 14 months. Our results show that our framework precisely aligns a significant number of images between surveys captured up to roughly three months apart, often across marked variation in appearance. Using these results, a human was able to spot several changes between surveys that would have otherwise gone unnoticed. [ABSTRACT FROM AUTHOR]

Articulation of 3D characters requires control over many degrees of freedom: a difficult task with standard 2D interfaces. We present a tangible input device composed of interchangeable, hot-pluggable parts. Embedded sensors measure the device's pose at rates suitable for real-time editing and animation. Splitter parts allow branching to accommodate any skeletal tree. During assembly, the device recognizes topological changes as individual parts or pre-assembled subtrees are plugged and unplugged. A novel semi-automatic registration approach helps the user quickly map the device's degrees of freedom to a virtual skeleton inside the character. User studies report favorable comparisons to mouse and keyboard interfaces for the tasks of target acquisition and pose replication. Our device provides input for character rigging and automatic weight computation, direct skeletal deformation, interaction with physical simulations, and handle-based variational geometric modeling. [ABSTRACT FROM AUTHOR]

Short-term changes in temporal and spatial distributions of the toxic cyanobacterium Planktothrix rubescens in Lake Zurich were investigated using high-resolution data sets acquired with an autonomous surface vessel (ASV). Data profiles were recorded with a multi-parameter probe while the ASV navigated along 1.5 km toward a waypoint located on the other side of the lake by using a global positioning system. We deployed the ASV seven times on five consecutive days during the stratification period (July 2011) to generate cross-sectional views of temperature, light, oxygen, and phycoerythrin and chlorophyll fluorescence from surface to 18 m. The data were also used to compute daily photosynthetic rates. Data showed a daily reshaping of the P. rubescens distribution in the metalimnion on both horizontal and vertical axes, from patches to a shore-to-shore spreading. A thermocline depression observed after 16 h of sustained winds forced the accumulation of P. rubescens on the downwind shore. The compression of the metalimnion and its downward shift by 6 m within 24 h suggested the modulation of a longitudinal seiche following the wind event. This passive transport of the metalimnetic P. rubescens population resulted in a 90% light reduction, and a decrease of the averaged daily photosynthetic rate from ±21 mmol O2m-2 d-1 to -10 mmol O2 m-2 d-1. Negative photosynthetic rates were computed on 2 d out of 5 d, meaning that the transport of P. rubescens by seiches significantly affected the balance between oxygen production and utilization in Lake Zurich, especially because it is the dominant primary producer. [ABSTRACT FROM AUTHOR]

The article discusses the navigation and control system for Avalon, an autonomous sailing vessel. It states that this boat was designed to compete in the Microtranstat Challenge and withstand the harsh condition of the Atlantic Ocean. It examines the vessel's robust mechanical design and navigation software which will create its optimal navigation course and control the boat in efficient manner. It adds that there is a demand for autonomous sailboats to be implemented in manned sailing vessels.

Owing to the fundamental nature of all-terrain exploration, autonomous rovers are confronted with unknown environments. This is especially apparent regarding soil interactions, as the nature of the soil is typically unknown. This work aims at establishing a framework from which the rover can learn from its interaction with the terrains encountered and shows the importance of such a method. We introduce a set of rover–terrain interaction (RTI) and remote data metrics that are expressed in different subspaces. In practice, the information characterizing the terrains, obtained from remote sensors (e.g., a camera) and local sensors (e.g., an inertial measurement unit) is used to characterize the respective remote data and RTI model. In each subspace, which can be described as a feature space encompassing either a remote data measurement or an RTI, similar features are grouped to form classes, and the probability distribution function over the features is learned for each one of those classes. Subsequently, data acquired on the same terrain are used to associate the corresponding models in each subspace and to build an inference model. Based on the remote sensor data measured, the RTI model is predicted using the inference model. This process corresponds to a near-to-far approach and provides the most probable RTI metrics of the terrain lying ahead of the rover. The predicted RTI metrics are then used to plan an optimal path with respect to the RTI model and therefore influence the rover trajectory. The CRAB rover is used in this work for the implementation and testing of the approach, which we call rover–terrain interactions learned from experiments (RTILE). This article presents RTILE, describes its implementation, and concludes with results from field tests that validate the approach. © 2009 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Tractor-trailer reversing is a classical nonlinear control problem in which many of the solutions proposed in the literature perform poorly in the presence of real-world constraints such as steering angle, rate limits, and lags. In this paper we describe a new method in which an inner loop controls the hitch angle of the trailer, creating a virtual articulated vehicle to which existing control techniques can be applied. We provide an analysis of the stability and convergence properties of this control approach, as well as experimental results that illustrate the robustness of this approach to model estimation errors, low-level control loop dynamics, and other disturbances introduced by, for example, state estimation errors. © 2008 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Hot metal carriers (HMCs) are large forklift-type vehicles used to move molten metal in aluminum smelters. This paper reports on field experiments that demonstrate that HMCs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. We present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. Two key experiments are described, lasting 2 and 5 h, in which the HMC traveled 15 km in total and handled the load 80 times. © 2008 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today's systems use target tracking algorithms based on object models. They work quite well in simple environments such as freeways, where few potential obstacles have to be considered. However, these approaches usually fail in more complex environments featuring a large variety of potential obstacles, as is usually the case in urban driving situations. In this paper we propose a new approach for robust perception and risk assessment in highly dynamic environments. This approach is called Bayesian occupancy filtering; it basically combines a four-dimensional occupancy grid representation of the obstacle state space with Bayesian filtering techniques. [ABSTRACT FROM AUTHOR]

A common way of localization in robotics is using triangulation on a system composed of a sensor and some landmarks (which can be artificial or natural). First, when no identifying marks are set on the landmarks, their identification by a robust algorithm is a complex problem which may be solved using correspondence graphs. Secondly, when the localization system has no a priori information about its environment, it has to build its own map in parallel with estimating its position, a problem known as simultaneous localization and mapping (SLAM). Recent works have proposed to solve this problem based on building a map made of invariant features. This paper describes the algorithms and data structure needed to deal with landmark matching, robot localization and map building in a single efficient process, unifying the previous approaches. Experimental results are presented using an outdoor robot car equipped with a two-dimensional scanning laser sensor. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which discusses various reports within the issue on topics including algorithm for determining the alignment between Doppler sonar velocity sensors and attitude sensors for underwater robots, calibration problem for underwater robots, and multi-modal sensor calibration using a gradient orientation measure.

Information about several papers discussed at the Sixth International Conference on Field and Service Robotics which was held in Chamonix, France on July 9-12, 2007 is presented. Topics include a robust method for extracting visual features of images taken by an omnidirectional camera, control problems in multi-robot systems, and solution provided by the Rao-Blackwellized particle filter. Moreover, the conference has provided a forum to exchange technical developments and experience in robotics.

The article discusses various reports published within the issue, including one about a new way to model the behavior of multiple agents seen as coupled dynamic systems, about problems of localizing robotic platform and about addressing the problem of planning trajectories for fast vehicles moving in a complex environment.

Background: Mobile genetic elements (MGEs) are widely involved in the dissemination of antibiotic resistance genes and some of them, such as the integrative and conjugative element SXT, are even induced by specific antibiotics at sub-lethal concentrations., Objectives: This work explores collateral effects of a broad range of antibiotics on the mobility of the SXTMO10 element using a specifically designed high-throughput screening test., Methods: Twenty-five promoters involved in the mobility of SXT and six artificial constitutive promoters were transcriptionally fused to luxCDABE bioluminescent genes and introduced into Escherichia coli strains with or without SXT to build whole-cell biosensors for a large-scale screening involving 48 antibiotics. A bioluminescent assay implementing a classical agar diffusion approach was coupled to an automated data processing pipeline developed to extract and analyse luminescence data from over 2000 antibiotic/biosensor combination profiles., Results: In addition to quinolones previously reported as inducing the expression of SXT mobility genes, we found that specific antibiotics belonging to other classes, such as imipenem and azithromycin, also behave as inducers. The use of a control set of constitutive biosensors also revealed an unexpected intricate relationship between cell respiration and light production that allowed the identification of antibiotics interfering with the respiration process., Conclusions: The effect of antibiotics goes beyond the interaction with their primary cell targets and may lead to adverse effects such as triggering the dissemination of resistance by MGEs, sometimes in unpredictable ways. Identifying such MGE-triggering antibiotics is of prime importance for better controlling collateral effects during therapy., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.)