Cardiovascular physiology of decapod crustaceans: from scientific inquiry to practical applications.

Until recently, the decapod crustacean heart was regarded as a simple, single ventricle, contraction of which forces haemolymph out into seven arteries. Differential tissue perfusion is achieved by contraction and relaxation of valves at the base of each artery. In this Review, we discuss recent work that has shown that the heart is bifurcated by muscular sheets that may effectively divide the single ventricle into 'chambers'. Preliminary research shows that these chambers may contract differentially; whether this enables selective tissue perfusion remains to be seen. Crustaceans are unusual in that they can stop their heart for extended periods. These periods of cardiac arrest can become remarkably rhythmic, accounting for a significant portion of the cardiac repertoire. As we discuss in this Review, in crustaceans, changes in heart rate have been used extensively as a measurement of stress and metabolism. We suggest that the periods of cardiac pausing should also be quantified in this context. In the past three decades, an exponential increase in crustacean aquaculture has occurred and heart rate (and changes thereof) is being used to understand the stress responses of farmed crustaceans, as well as providing an indicator of disease progression. Furthermore, as summarized in this Review, heart rate is now being used as an effective indicator of humane methods to anaesthetize, stun or euthanize crustaceans destined for the table or for use in scientific research. We believe that incorporation of new biomedical technology and new animal welfare policies will guide future research directions in this field.

Diagnostic sample transport via pneumatic tube systems: data logger and their algorithms are sensitive to transport effects.

OBJECTIVES: Many hospitals use pneumatic tube systems (PTS) for transport of diagnostic samples. Continuous monitoring of PTS and evaluation prior to clinical use is recommended. Data loggers with specifically developed algorithms have been suggested as an additional tool in PTS evaluation. We compared two different data loggers. METHODS: Transport types - courier, conventional (cPTS) and innovative PTS (iPTS) - were monitored using two data loggers (MSR145® logger, CiK Solutions GmbH, Karlsruhe, Germany, and a prototype developed at the University Medicine Greifswald). Data loggers differ in algorithm, recording frequencies and limit of acceleration detection. Samples from apparently healthy volunteers were split among the transport types and results for 37 laboratory measurands were compared. RESULTS: For each logger specific arbitrary units were calculated. Area-under-the-curve (AUC)-values (MSR145®) were lowest for courier and highest for iPTS and increased with increasing recording frequencies. Stress (St)-values (prototype logger) were obtained in kmsu (1,000*mechanical stress unit) and were highest for iPTS as well. Statistical differences between laboratory measurement results of transport types were observed for three measurands sensitive for hemolysis. CONCLUSIONS: The statistical, but not clinical, differences in the results for hemolysis sensitive measurands may be regarded as an early sign of preanalytical impairment. Both data loggers record this important interval of beginning mechanical stress with a high resolution indicating their potential to facilitate early detection of preanalytical impairment. Further studies should identify suitable recording frequencies. Currently, evaluation and monitoring of diagnostic sample transport should not only rely on data loggers but also include diagnostic samples.

Reliability Testing of a Low-Cost, Multi-Purpose Arduino-Based Data Logger Deployed in Several Applications Such as Outdoor Air Quality, Human Activity, Motion, and Exhaust Gas Monitoring.

This contribution shows the possibilities of applying a low-cost, multi-purpose data logger built around an Arduino Mega 2560 single-board computer. Most projects use this kind of hardware to develop single-purpose data loggers. In this work, a data logger with a more general hardware and software architecture was built to perform measurement campaigns in very different domains. The wide applicability of this data logger was demonstrated with short-term monitoring campaigns in relation to outdoor air quality, human activity in an office, motion of a journey on a bike, and exhaust gas monitoring of a diesel generator. In addition, an assessment process and corresponding evaluation framework are proposed to assess the credibility of low-cost scientific devices built in-house. The experiences acquired during the development of the system and the short measurement campaigns were used as inputs in the assessment process. The assessment showed that the system scores positively on most product-related targets. However, unexpected events affect the assessment over the longer term. This makes the development of low-cost scientific devices harder than expected. To assure stability and long-term performance of this type of design, continuous evaluation and regular engineering corrections are needed throughout longer testing periods.

Microclimatic conditions mediate the effect of deadwood and forest characteristics on a threatened beetle species, Tragosoma depsarium.

While climate change has increased the interest in the influence of microclimate on many organisms, species inhabiting deadwood have rarely been studied. Here, we explore how characteristics of forest stands and deadwood affect microclimate inside deadwood, and analyse how this affects wood-living organisms, exemplified by the red-listed beetle Tragosoma depsarium. Deadwood and forest variables explained much of the variation in temperature, but less of the variation in moisture within deadwood. Several variables known to influence habitat quality for deadwood-dependent species were found to correlate with microclimate. Standing deadwood and an open canopy generates warmer conditions in comparison to downed logs and a closed canopy, and shaded, downed and large-diameter wood have higher moisture and more stable daily temperatures than sun-exposed, standing, and small-diameter wood. T. depsarium occupancy and abundance increased with colder and more stable winter temperatures, and with higher spring temperatures. Consistently, the species occurred more frequently in deadwood items with characteristics associated with these conditions, i.e. downed large-diameter logs occurring in open conditions. Conclusively, microclimatic conditions were found to be important for a deadwood-dependent insect, and related to characteristics of both forest stands and deadwood items. Since microclimate is also affected by macroclimatic conditions, we expect species' habitat requirements to vary locally and regionally, and to change due to climate warming. Although many saproxylic species preferring sun-exposed conditions would benefit from a warmer climate per se, changes in species interactions and land use may still result in negative net effects of climate warming.

THERMOD: Development of a Cost Effective Solution for Integrated Sensing and Logging.

With the outbreak of the Covid-19 pandemic, vaccination has become mandatory. Further, for effective results, the vaccines should be stored within the recommended temperature range, typically between 2°C to 8°C, transported safely without any mishandling and temperature excursion. In order to assure vaccine potency, it is essential to have detailed information on the entire temperature data recorded at user-defined intervals. In this paper, we develop functionality interaction to bring different sensors, memory, and processing units to an integrated platform, providing a compact, power-efficient, and low-cost commercial TemperatuRE, Humidity, and MOvement Data-logger (THERMOD). Moreover, the THERMOD hardware is packed with interactive algorithms that address the aforementioned concerns and log the real-time temperature and jerks (3-dimensional movement) encountered throughout the journey, and the logged data can be retrieved by plugging THERMOD into the host computer/laptop. The THERMOD hardware formulation and algorithm embedding have been done in the institution lab, which enables end-to-end storage and monitoring. Also, the proposed design is built with the defined standards by health organizations, e.g., WHO. Further, to validate the proficiency of the proposed design, comparative analysis has been done; a) a cost analysis has been done to state the cost efficiency of the proposed solution, b) real-time power performance graphs have been plotted which depict that THERMOD outperforms the existing solutions. Moreover, a number of experiments were performed for the validation of the proposed design.

Multimodal Functional Analysis Platform: 3. Spherical Treadmill System for Small Animals.

In the application of advanced neuroscience techniques including optogenetics to small awake animals, it is often necessary to restrict the animal's movements. A spherical treadmill is a beneficial option that enables virtual locomotion of body- or head-restrained small animals. Besides, it has a wide application range, including virtual reality experiments. This chapter describes the fundamentals of a spherical treadmill for researchers who want to start experiments with it. First, we describe the physical aspect of a spherical treadmill based on the simple mechanical analysis. Next, we explain the basics of data logging and preprocessing for behavioral analysis. We also provide simple computer programs that work for the purpose.

Development of a Low-Power Underwater NFC-Enabled Sensor Device for Seaweed Monitoring.

Aquaculture farming faces challenges to increase production while maintaining welfare of livestock, efficiently use of resources, and being environmentally sustainable. To help overcome these challenges, remote and real-time monitoring of the environmental and biological conditions of the aquaculture site is highly important. Multiple remote monitoring solutions for investigating the growth of seaweed are available, but no integrated solution that monitors different biotic and abiotic factors exists. A new integrated multi-sensing system would reduce the cost and time required to deploy the system and provide useful information on the dynamic forces affecting the plants and the associated biomass of the harvest. In this work, we present the development of a novel miniature low-power NFC-enabled data acquisition system to monitor seaweed growth parameters in an aquaculture context. It logs temperature, light intensity, depth, and motion, and these data can be transmitted or downloaded to enable informed decision making for the seaweed farmers. The device is fully customisable and designed to be attached to seaweed or associated mooring lines. The developed system was characterised in laboratory settings to validate and calibrate the embedded sensors. It performs comparably to commercial environmental sensors, enabling the use of the device to be deployed in commercial and research settings.

An Open-Source, Durable, and Low-Cost Alternative to Commercially Available Soil Temperature Data Loggers.

Soil temperatures play an important role in determining the distribution and function of organisms. However, soil temperature is decoupled from air temperature and varies widely in space. Characterizing and predicting soil temperature requires large and expensive networks of data loggers. We developed an open-source soil temperature data logger and created online resources to ensure our design was accessible. We tested data loggers constructed by students, with little prior electronics experience, in the lab, and in the field in Alaska. The do-it-yourself (DIY) data logger was comparably accurate to a commercial system with a mean absolute error of 2% from -20-0 °C and 1% from 0-20 °C. They captured accurate soil temperature data and performed reliably in the field with less than 10% failing in the first year of deployment. The DIY loggers were ~1.7-7 times less expensive than commercial systems. This work has the potential to increase the spatial resolution of soil temperature monitoring and serve as a powerful educational tool. The DIY soil temperature data logger will reduce data collection costs and improve our understanding of species distributions and ecological processes. It also provides an educational resource to enhance STEM, accessibility, inclusivity, and engagement.

Prediction of Tool Forces in Manual Grinding Using Consumer-Grade Sensors and Machine Learning.

Tool forces are a decisive parameter for manual grinding with hand-held power tools, which can be used to determine the productivity, quality of the work result, vibration exposition, and tool lifetime. One approach to tool force determination is the prediction of tool forces via measured operating parameters of a hand-held power tool. The problem is that the accuracy of tool force prediction with consumer-grade sensors remains unclear in manual grinding. Therefore, the accuracy of tool force prediction using Gaussian process regression is examined in a study for two hand-held angle grinders in four different applications in three directions using measurement data from an inertial measurement unit, a current sensor, and a voltage sensor. The prediction of the grinding normal force (rMAE = 11.44% and r = 0.84) and the grinding tangential force (rMAE = 18.21% and r = 0.82) for three tested applications, as well as the radial force for the application cutting with a cut-off wheel (rMAE = 19.67% and r = 0.80) is shown to be feasible. The prediction of the guiding force (rMAE = 87.02% and r = 0.37) for three tested applications is only possible to a limited extent. This study supports data acquisition and evaluation of hand-held power tools using consumer-grade sensors, such as an inertial measurement unit, in real-world applications, resulting in new potentials for product use and product development.

The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation.

In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually observed. Our results highlight that the random forest model is a valid and robust approach to predict the feeding behaviour of the whale shark. In conclusion this novel approach exposes the practicality of this method to serve as a conservation tool and the capability it offers in monitoring potential disturbances of the species.

Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture.

Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world's growing population while limiting environmental pollution. The aim of this paper is to describe a multi-sensor Internet of Things (IoT) system for agriculture consisting of a soil probe, an air probe and a smart data logger. The implementation details will focus of the integration element and the innovative Artificial Intelligence based gas identification sensor. Furthermore, the paper focuses on the analytics and decision support system implementation that provides farming recommendations and is enhanced with a feedback loop from farmers and a social trust index that will increase the reliability of the system.

The Advanced Prototype of the Geohydroacoustic Ice Buoy.

The new-generation geohydroacoustic buoy prototype is designed for simultaneous acquisition of acoustic, hydroacoustic, and seismoacoustic data in various environmental conditions, including onshore and offshore boreholes, yet is specifically targeted for operation in Arctic seas as an element of the distributed ice-class drifting antennas. Modular structure of the geohydroacoustic ice buoy incorporates the advanced data logger and a combination of sensors: vector-scalar hydroacoustic (0.01-2.5 kHz) accelerometer, broadband molecular-electronic (0.03-50 Hz) velocimeter, as well as optional hydrophones. The distinguishing feature of the geohydroacoustic buoy is its low power consumption responsible for consistent autonomous operation of the entire measurement system for at least one week. Results of continuous laboratory tests carried out at the geophysical observatory of the Geophysical Survey of the Russian Academy of Sciences (GS RAS) in Obninsk are presented. It has been confirmed via comparative analysis of recorded time series featuring microseismic noise and teleseismic earthquakes that the prototype well meets the high standards of modern seismology.

SenseJoy, a pluggable solution for assessing user behavior during powered wheelchair driving tasks.

BACKGROUND: The complex task of Electric Powered Wheelchairs (EPW) prescription relies mainly on personal experience and subjective observations despite standardized processes and protocols. The most informative measurements come from joystick monitoring, but recording direct joystick outputs require to disassemble the joystick. We propose a new solution called "SenseJoy" that is easy to plug on a joystick and is suitable to characterize the driver behavior by estimating the joystick command. METHODS: SenseJoy is a pluggable system embedded on EPW built with a 3D accelerometer and a 2D gyrometer placed within the joystick and another 3D accelerometer located at the basis of the joystick. Data is sampled at 39 Hz and processed offline. First, SenseJoy sensitivity is assessed on wheelchair driving tasks performed by a group of 8 drivers (31 ± 8 years old, including one driver with left hemiplegia, one with cerebral palsy) in a lab environment. Direct joystick measurements are compared with SenseJoy estimations in different driving exercises. A second group of 5 drivers is recorded in the ecological context of a rehabilitation center (41 ± 10 years old, with two tetraplegic drivers, one tetraplegic driver with cognitive disorder, one driver post-stroke, one driver with right hemiplegia). The measurements from all groups of drivers are evaluated with an unsupervised statistical analysis, to estimate driving profile clusters. RESULTS: The SenseJoy is able to measure the EPW joystick inclination angles with a resolution of 1.31% and 1.23% in backward/forward and left/right directions respectively. A statistical validation ensures that the classical joystick-based indicators are equivalent when acquired with the SenseJoy or with a direct joystick output connection. Using an unsupervised methodology, based on a similarity matrix between subjects, it is possible to characterize the driver profile from real data. CONCLUSION: SenseJoy is a pluggable system for assessing the joystick controls during EPW driving tasks. This system can be plugged on any EPW equipped with a joystick control interface. We demonstrate that it correctly estimates the performance indicators and it is able to characterize driving profile. The system is suitable and efficient to assist therapists in their recommendation, by providing objective measures with a fast installation process.

Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger.

The main objective of this paper is to compensate power factor using teaching learning based optimization (TLBO), determine the capacitor bank optimization (CBO) algorithm, and monitor a system in real-time using cloud data logging (CDL). Implemented Power Factor Compensation and Monitoring System (PFCMS) calculates the optimal capacitor combination to improve power factor of the installation by measure of voltage, current, and active power. CBO algorithm determines the best solution of capacitor values to install, by applying TLBO in different phases of the algorithm. Electrical variables acquired by the sensors and the variables calculated are stored in CDL using Google Sheets (GS) to monitor and analyse the installation by means of a TLBO algorithm implemented in PFCMS, that optimizes the compensation power factor of installation and determining which capacitors are connected in real time. Moreover, the optimization of the power factor in facilities means economic and energy savings, as well as the improvement of the quality of the operation of the installation.

Supraclavicular skin temperature measured by iButtons and 18F-fluorodeoxyglucose uptake by brown adipose tissue in adults.

Currently, 18 [F]-Fluorodeoxyglucose (18F-FDG) in combination with a positron emission tomography/computed tomography (PET/CT) scan analysis is the most commonly used method to quantify human BAT volume and activity. However, this technique presents several drawbacks which negatively affect participant's health. The aim of the present work is to determine whether supraclavicular skin temperature can be used as an indirect marker of cold-induced BAT and skeletal muscle 18F-FDG uptake in adults, while taking into account body composition. We performed a personalized cooling protocol just before an 18F-FDG-PET/CT scan, and we measured supraclavicular skin temperature before (in warm conditions) and after the cooling protocol in 88 adults (n = 57 women, mean age: 21.9 ±â€¯2.1 years old, body mass index: 24.5 ±â€¯4.3 km/m2). We found that supraclavicular skin temperature at the warm and cold periods was weakly and positively associated with BAT activity (SUVmean and SUVpeak: ß = 3.000; R2 = 0.072; P = 0.022 and ß = 2.448; R2 = 0.060; P = 0.021), but not with skeletal muscle 18F-FDG uptake, after controlling for body composition. We performed further analyses and the positive associations persisted only in the group of women. In conclusion, supraclavicular skin temperature in warm and cold conditions seems to be related with cold-induced 18F-FDG uptake by BAT only in women, although the low explained variance of these associations means that there are other factors involved in the supraclavicular skin temperature.

A Low-Cost Data Acquisition System for Automobile Dynamics Applications.

This project addresses the need for the implementation of low-cost acquisition technology in the field of vehicle engineering: the design, development, manufacture, and verification of a low-cost Arduino-based data acquisition platform to be used in <80 Hz data acquisition in vehicle dynamics, using low-cost accelerometers. In addition to this, a comparative study is carried out of professional vibration acquisition technologies and low-cost systems, obtaining optimum results for low- and medium-frequency operations with an error of 2.19% on road tests. It is therefore concluded that these technologies are applicable to the automobile industry, thereby allowing the project costs to be reduced and thus facilitating access to this kind of research that requires limited resources.

Cave Pearl Data Logger: A Flexible Arduino-Based Logging Platform for Long-Term Monitoring in Harsh Environments.

A low-cost data logging platform is presented that provides long-term operation in remote or submerged environments. Three premade "breakout boards" from the open-source Arduino ecosystem are assembled into the core of the data logger. Power optimization techniques are presented which extend the operational life of this module-based design to >1 year on three alkaline AA batteries. Robust underwater housings are constructed for these loggers using PVC fittings. Both the logging platform and the enclosures, are easy to build and modify without specialized tools or a significant background in electronics. This combination turns the Cave Pearl data logger into a generalized prototyping system and this design flexibility is demonstrated with two field studies recording drip rates in a cave and water flow in a flooded cave system. This paper describes a complete DIY solution, suitable for a wide range of challenging deployment conditions.

Assessment of MRI issues at 1.5 T for the Temperature Logger Implant.

PURPOSE: The Temperature Logger Implant is a newly developed device that is capable of providing data for animal studies on thermoregulatory function, hibernation, hypothermia, and general health. During research, it may be necessary to conduct a magnetic resonance imaging (MRI) examination on an animal with this device implanted to assess anatomical changes or other conditions. Notably, this new device was specially designed to be unaffected by the electromagnetic fields used for MRI. Therefore, to verify that there would be no problems related to MRI, the purpose of this investigation was to evaluate MRI-related issues for the Temperature Logger Implant. METHODS: Tests were performed on the Temperature Logger Implant using well-accepted techniques to evaluate magnetic field interactions (translational attraction and torque, 1.5 T), MRI-related heating (whole body averaged specific absorption rate, 2.9 W/kg), artifacts (T1-weighted, spin echo and gradient echo pulse sequences), and functional changes related to exposure to eight different imaging conditions. RESULTS: Magnetic field interactions were relatively low (deflection angle 4°, no torque) and heating was minor (highest temperature rise, > 1.1 °C) indicating that these factors will not pose a hazard to an animal. The largest artifact (gradient echo pulse sequence) extended 10 mm from the size and shape of the Temperature Logger Implant. Exposure to the eight different conditions at 1.5 T/ 64 MHz did not alter or damage the operational aspects of the device. CONCLUSIONS: The findings demonstrated that MRI can be performed safely on an animal with this new Temperature Logger Implant and, thus, this device is deemed "MR Conditional" (i.e., using current labeling terminology), according to the conditions used in this investigation.

Metabolic rates and the energetic cost of external tag attachment in juvenile blacktip sharks Carcharhinus limbatus.

This study reports on the metabolic rate of the blacktip shark Carcharhinus limbatus and the energetic costs of external tag attachment. Metabolic rates, swimming speed and tail-beat (BT ) frequency were measured in a static respirometer with untagged animals and animals equipped with a small data logger. Tagged sharks showed significantly higher routine oxygen consumption and lower swimming speeds than untagged animals, indicating that tagging significantly affected the swimming efficiency and energetic requirements in these small sharks, and that these effects must be accounted for when interpreting telemetry data from free-ranging individuals.

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes.

The ability to produce estimates of the metabolic rate of free-ranging animals is fundamental to the study of their ecology. However, measuring the energy expenditure of animals in the field has proved difficult, especially for aquatic taxa. Accelerometry presents a means of translating metabolic rates measured in the laboratory to individuals studied in the field, pending appropriate laboratory calibrations. Such calibrations have only been performed on a few fish species to date, and only one where the effects of temperature were accounted for. Here, we present calibrations between activity, measured as overall dynamic body acceleration (ODBA), and metabolic rate, measured through respirometry, for nurse sharks (Ginglymostoma cirratum), lemon sharks (Negaprion brevirostris) and blacktip sharks (Carcharhinus limbatus). Calibrations were made at a range of volitional swimming speeds and experimental temperatures. Linear mixed models were used to determine a predictive equation for metabolic rate based on measured ODBA values, with the optimal model using ODBA in combination with activity state and temperature to predict metabolic rate in lemon and nurse sharks, and ODBA and temperature to predict metabolic rate in blacktip sharks. This study lays the groundwork for calculating the metabolic rate of these species in the wild using acceleration data.