On-board Analysis Research Articles

Simultaneous onboard analysis of seawater dissolved inorganic carbon (DIC) concentration and stable isotope ratio (δ13C‐DIC)

AbstractDissolved inorganic carbon (DIC) and its stable carbon isotope (δ13C‐DIC) are valuable parameters for studying the aquatic carbon cycle and quantifying ocean anthropogenic carbon accumulation rates. However, the potential of this coupled pair is underexploited as only 15% or less of cruise samples have been analyzed for δ13C‐DIC because the traditional isotope analysis is labor‐intensive and restricted to onshore laboratories. Here, we improved the analytical precision and reported the protocol of an automated, efficient, and high‐precision method for ship‐based DIC and δ13C‐DIC analysis based on cavity ring‐down spectroscopy (CRDS). We also introduced a set of stable in‐house standards to ensure accurate and consistent DIC and δ13C‐DIC measurements, especially on prolonged cruises. With this method, we analyzed over 1600 discrete seawater samples over a 40‐d cruise along the North American eastern ocean margin in summer 2022, representing the first effort to collect a large dataset of δ13C‐DIC onboard of any oceanographic expedition. We evaluated the method's uncertainty, which was 1.2 μmol kg−1 for the DIC concentration and 0.03‰ for the δ13C‐DIC value (1σ). An interlaboratory comparison of onboard DIC concentration analysis revealed an average offset of 2.0 ± 3.8 μmol kg−1 between CRDS and the coulometry‐based results. The cross‐validation of δ13C‐DIC in the deep‐ocean data exhibited a mean difference of only −0.03‰ ± 0.07‰, emphasizing the consistency with historical data. Potential applications in aquatic biogeochemistry are discussed.

Mechanical Method for Rapid Determination of Step Count Sensor Settings.

With the increased push for personalized medicine, researchers and clinicians have begun exploring the use of wearable sensors to track patient activity. These sensors typically prioritize device life over robust onboard analysis, which results in lower accuracies in step count, particularly at lower cadences. To optimize the accuracy of activity-monitoring devices, particularly at slower walking speeds, proven methods must be established to identify suitable settings in a controlled and repeatable manner prior to human validation trials. Currently, there are no methods for optimizing these low-power wearable sensor settings prior to human validation, which requires manual counting for in-laboratory participants and is limited by time and the cadences that can be tested. This article proposes a novel method for determining sensor step counting accuracy prior to human validation trials by using a mechanical camshaft actuator that produces continuous steps. Sensor error was identified across a representative subspace of possible sensor setting combinations at cadences ranging from 30 steps/min to 110 steps/min. These true errors were then used to train a multivariate polynomial regression to model errors across all possible setting combinations and cadences. The resulting model predicted errors with an R2 of 0.8 and root-mean-square error (RMSE) of 0.044 across all setting combinations. An optimization algorithm was then used to determine the combinations of settings that produced the lowest RMSE and median error for three ranges of cadence that represent disabled low-mobility ambulators, disabled high-mobility ambulators, and healthy ambulators (30-60, 20-90, and 30-110 steps/min, respectively). The model identified six setting combinations for each range of interest that achieved a ±10% error in cadence prior to human validation. The anticipated range of errors from the optimized settings at lower walking speeds are lower than the reported errors of wearable sensors (±30%), suggesting that pre-human-validation optimization of sensors may decrease errors at lower cadences. This method provides a novel and efficient approach to optimizing the accuracy of wearable activity monitors prior to human validation trials.

DeepLOKI- a deep learning based approach to identify zooplankton taxa on high-resolution images from the optical plankton recorder LOKI

Zooplankton play a crucial role in the ocean’s ecology, as they form a foundational component in the food chain by consuming phytoplankton or other zooplankton, supporting various marine species and influencing nutrient cycling. The vertical distribution of zooplankton in the ocean is patchy, and its relation to hydrographical conditions cannot be fully deciphered using traditional net casts due to the large depth intervals sampled. The Lightframe On-sight Keyspecies Investigation (LOKI) concentrates zooplankton with a net that leads to a flow-through chamber with a camera taking images. These high-resolution images allow for the determination of zooplankton taxa, often even to genus or species level, and, in the case of copepods, developmental stages. Each cruise produces a substantial volume of images, ideally requiring onboard analysis, which presently consumes a significant amount of time and necessitates internet connectivity to access the EcoTaxa Web service. To enhance the analyses, we developed an AI-based software framework named DeepLOKI, utilizing Deep Transfer Learning with a Convolution Neural Network Backbone. Our DeepLOKI can be applied directly on board. We trained and validated the model on pre-labeled images from four cruises, while images from a fifth cruise were used for testing. The best-performing model, utilizing the self-supervised pre-trained ResNet18 Backbone, achieved a notable average classification accuracy of 83.9%, surpassing the regularly and frequently used method EcoTaxa (default) in this field by a factor of two. In summary, we developed a tool for pre-sorting high-resolution black and white zooplankton images with high accuracy, which will simplify and quicken the final annotation process. In addition, we provide a user-friendly graphical interface for the DeepLOKI framework for efficient and concise processes leading up to the classification stage. Moreover, performing latent space analysis on the self-supervised pre-trained ResNet18 Backbone could prove advantageous in identifying anomalies such as deviations in image parameter settings. This, in turn, enhances the quality control of the data. Our methodology remains agnostic to the specific imaging end system used, such as Loki, UVP, or ZooScan, as long as there is a sufficient amount of appropriately labeled data available to enable effective task performance by our algorithms.

Status of the H2020-ROBOMINERS Prototype

This article presents the current status of the H2020-ROBOMINERS project with focus on the prototype to be developed. The aim of this project is the development of a small-scale mining robot, which will be capable of exploring difficult to access deposits with the ability of selective mining underground, under water, and in slurries. Considerably low weight and power are challenges to be overcome. Environment-friendliness is secured by powering the entire robot water-hydraulically. Core element of the robominer is the main module, in which the locomotion and powering system will be implemented. Additional elements in the robot are sensors for navigation and perception and a production tool to excavate small amounts of material. The locomotion system consists of an Archimedes-screw mechanism, which can be extended in radial direction and used as grippers inside a tunnel to increase its traction capacity. Selective perception tools help the mining robot navigate in harsh terrains and find the ore. A small-scale longitudinal part-face cutter head has been selected as an excavation tool. This cutter head has been tested extensively in the laboratory by performing cutting tests with several rock samples. The performance allows a continuous excavation of soft rock material (successful tests with reasonable excavation rate up to a uniaxial compressive strength of 30 MPa). The mined ore is then slurrified and transported to a processing station. On-board analysis equipment using specializsed sensing systems allows the robot to analyse the slurry composition in real-time. The demonstration and final test of the full-scale prototype are planned in an open-pit oilshale mine. Eventually, the project will serve as a guideline for future mining robots including feasibility studies of different robot designs, potential mine layouts and mining scenarios as well as various excavation tools for different rock conditions.

Evaluation of enamel thickness of mandibular incisors.

To measure enamel thickness at the proximal surfaces of the mandibular incisors, using micro-computed tomography (micro-CT) scans. Forty-one single-rooted mandibular incisors were selected and analyzed according to anatomical characteristics, to form three groups: Group 1 - central incisors (n = 18); Group 2 - right lateral incisors (n = 10); and Group 3 - left lateral incisors (n = 13). First, enamel thickness at the proximal contact areas of the mandibular incisors was measured. Second, the mesial and distal surfaces of the lateral incisors were compared. Finally, the relationship between the tooth width and the mean enamel thickness was determined. Each tooth was scanned with a micro-CT scanner, and the image was processed with SCANCO micro-CT onboard analysis software. There were no statistically significant differences in mean enamel thickness between the mesial and distal surfaces for each lateral incisor, or between contralateral lateral incisors. In all surfaces analyzed, the upper zones had statistically significantly thinner enamel (0.52 ± 0.10 mm) when compared to the middle and lower zones (0.60 ± 0.08 mm and 0.59 ± 0.08 mm, respectively). There was no correlation (r =0.07) between enamel thickness of the mandibular incisor and the tooth width. The enamel thickness of the mandibular incisors is similar on the mesial and distal surfaces, with the thinnest layer located at the upper zone.

Lithium-sulfur battery diagnostics through distribution of relaxation times analysis

• Distribution of relaxation times (DRT) is a powerful tool for deconvolution relaxation processes occurring in the overlapping frequency region in the EIS. • DRT peaks are correlated to the specific electrode process through analysis of relaxation processes in symmetric cells and evolution of the DRT profile of a fresh cell at different state-of-charge. • Impedance features of a pristine cell are dominated by the Li metal negative electrode and by the positive electrode after the initial charge-discharge. • Flooded electrolyte improves electrode kinetics and ion diffusion while lean electrolyte conditions cause high polarization throughout the discharge. Electrochemical impedance spectroscopy (EIS) is widely used in battery analysis as it is simple to implement and non-destructive. However, the data provided is a global representation of all electrochemical processes within the cell and much useful information is ambiguous or inaccessible when using traditional analysis techniques. This is a major challenge when EIS is used to analyse systems with complex cell chemistries, like lithium-sulfur (Li-S), one of the strongest candidates to supersede conventional Li-ion batteries. Here we demonstrate the application of distribution of relaxation times (DRT) analysis for quantitative deconvolution of EIS spectra from Li-S batteries, revealing the contributions of (eight) distinct electrode processes to the total cell polarisation. The DRT profile is shown to be strongly dependent on cell state-of-charge, offering a route to automated and on-board analysis of Li-S cells.

Internet of Things in Sport Training: Application of a Rowing Propulsion Monitoring System

The application of electronics, communication, and telemetry technologies in the field of sport training is a major trend today, specially with the explosion of the Internet of Things (IoT) paradigm. In particular, the rowing sport is one of the disciplines that could benefit from efficient, easy to integrate, and low cost IoT technologies to help analyzing and optimizing the performance of the rowers. However, traditionally monitoring tools in rowing are expensive and very limited. In this work, a rowing propulsion monitoring system for onboard analysis of rower’s key parameters is proposed, based on the development of a low-cost IoT device that combines sensing, global positioning, wireless communication, and data fusion for runtime information processing and monitoring on the boat. A power calculation model during the stroke is also proposed in order to estimate the energetic efficiency of the strokes in relation with the boat velocity. An acceleration sensor on the oar is used to decompose the movement; a torsion sensor to calculate the rower’s strength and energetic values; and navigation data for speed and distance values of the boat. A comprehensive comparative experimentation in a real rowing training scenario is performed, applying the proposed system and considering various rowers. The results show that the device provides a good vision in time of the movement and also very valuable technical information that can be used by rowers and trainers to define specific optimization profiles and improvement targets.

Performance evaluation of a shaped sonic boom detector and classifier

NASA will soon fly the X-59 aircraft over selected communities to evaluate community responses to shaped sonic booms. Community tests will include dozens of deployed acoustic sensors capable of measuring and detecting shaped sonic boom waveforms in situ for rapid onboard analysis. To this end, we present a sonic boom detector and classifier. The sonic boom detector identifies a shaped sonic boom within a measured acoustical waveform by calculating the cross-correlation with a template shaped sonic boom waveform. The sonic boom classifier determines whether the identified event is indeed a shaped sonic boom based on the correlation coefficient and the calculated noise exposure level. We evaluate these algorithms using simulations of on- and off-design X-59 sonic boom waveforms injected into previously measured 30 s ambient noise recordings. Results of this case study indicate that the detector identifies a sonic boom with an accuracy of ±100 ms in 99.98% of the cases. Furthermore, for a given 30 s measurement, the classifier shows true-positive rates of approximately 0.9999 when the false-positive rate is 10−3. The case study demonstrates that the recommended onboard sonic boom detector and classifier should be highly capable of identifying shaped sonic booms.

Characterization and classification of estuarine suspended particles based on their inorganic/organic matter composition

An 11 hours survey was performed on the 17th of September 2014 in the Rhine Region Of Freshwater Influence (Rhine-ROFI) about 10 km downstream of the mouth of the Rotterdam Waterway during calm weather conditions. Suspended Particle Matter (SPM) measurements were performed during a full tidal cycle, near the seabed, at neap tide, and samples were taken at 0.6 meter above bed for on-board analysis. The measurements were performed with (a) LISST 100X, a submersible particle size analyzer, (b) LISST-HOLO, a submersible digital holographic camera, (c) a home-made underwater camera and (d) an on-board LabSFLOC2 video microscopy equipment that used in-situ collected samples. The first aim of the present study was to compare the results obtained from the different monitoring techniques and to characterize the different types of suspended particles found in-situ. It was found that that the highly anisotropic particles present in the water column lead to multiple peaks in the Particle Size Distributions (PSD) found using the LISST 100X. Using the LISST-HOLO, underwater camera and LabSFLOC2 camera these particles could properly be imaged and meaningful PSD’s were obtained using these techniques in the size range > 20 μm. LabSFLOC2, LISST-HOLO and the underwater camera moreover provide information on the size and aspect ratio of particles. On the other hand, LISST 100X can be used to detect the fine fraction (<20 μm), a size range that is not accessible for the other techniques. From the analysis of the data on the survey day, three classes of particles were identified, based on composition rather than size (the sizes given here are purely indicative): (1) mineral (inorganic) sediment particles in the range size 5 - 20 μm, (2) organic/inorganic aggregates in the size range 20 - 200 μm and (3) organic particles in the size range > 200 μm. A large range of settling velocities (0.1 - 10 mm/s) and aspect ratios between 1 and 10 were recorded by video microscopy (LabSFLOC2). This spreading in settling velocities and aspect ratio was due to the different properties (shape, effective density and size) of the particles in the water column. The second aim of the study was to reproduce the flocs found in-situ in the lab and investigate the kinetics of flocculation between inorganic and living organic matter. Laboratory experiments were conducted with grab samples obtained from Port of Rotterdam harbour and living microalgae (Skeletonema costatum). The results of these experiments showed a shift in effective density upon addition of living algae to the sediment, which confirmed the flocculation ability between sediment and microalgae. The flocculation occured on a timescale of minutes and lead to flocs having a large spread in density for a given size, due to the heteregeous inorganic/organic composition of the flocs. This spread in density was at the origin of the large range of settling velocities for a given floc size observed in-situ, which leads to conclude that organic matter should be an important input parameter in sediment transport models.

Cryogenic freezing: A reliable preservation method of samples for seawater nutrient analysis

AbstractFreezing is a strongly recommended preservation method of samples for seawater nutrient analysis when onboard analysis is not available. Previous studies on the effects of freezing methods have explored issues including freezing period, prefiltration, and freezing speed. In this study, the effects of various freezing and storage temperatures on seawater nutrient analysis were examined using a domestic freezer (−18°C), scientific freezer (−23°C), and cryogenic freezer (−80°C). The results showed no difference between the fresh and frozen samples stored in the cryogenic freezer. The observed differences between samples from the domestic freezer and those from the scientific freezers can be attributed to the freezer auto‐defrost function. Transferring samples between the scientific and cryogenic freezers maintained their condition during freezing and storage when a scientific freezer without an auto‐defrost function was used. Silicate concentrations in frozen samples in the cryogenic freezer were similar to those of the fresh samples, even when the frozen samples were analyzed several hours after thawing. Therefore, a cryogenic freezer is highly recommended for freezing and storing seawater nutrient samples because of its stability and independence from silicate polymer formation.

A miniaturized radiation monitor for continuous dosimetry and particle identification in space

A Miniaturized Radiation Monitor (MIRAM) has been developed for the continuous measurement of the radiation field composition and ionizing dose rates in near earth orbits. Compared to currently used radiation monitors, the presented device has an order of magnitude lower weight while being comparable in power consumption and functionality. MIRAM is capable of on-board real-time self-diagnostic. Furthermore, it supports on-board analysis of the measured data to be able to work autonomously. The dose rate is calculated continuously based on the energy deposition in the Timepix3 detector. For the estimation of the particle species composition of the radiation environment, two methods are applied depending on the current flux. At lower fluxes (<104 particles per cm2 per s), a track-by-track analysis based on temporal coincidence is applied. At higher fluxes, a less power and memory consuming method is utilized. This method is using the averaged deposited energy per pixel to estimate the electron and proton content of the radiation field.

Reconfigurable Framework for Resilient Semantic Segmentation for Space Applications

Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.

Field determination of inorganic mercury in seawaters by a portable dual-channel and purge-and-trap system with atomic fluorescence spectrometry

ABSTRACT An on-line flow injection mercury analyser (FIMA) for inorganic mercury (Hg) analysis in environmental waters is presented. The FIMA is a portable dual-channel and purge-and-trap system combining aqueous reduction with stannous chloride (SnCl2), two-stage gold (Au) amalgamation, thermal desorption of Hg0 and final detection with cold vapour atomic fluorescence spectrometry (CVAFS). Simultaneous on-line operations of sample loading and analysis make analytical throughput and accuracy improved and contamination eliminated. Results of system optimisation and reliability regarding the determination of inorganic Hg2+ are described. Analytical performances of both channels were the same in terms of data reliability. Low procedural blanks were obtained from laboratory and field trip (≤5 pg, n = 30). Excellent calibrations (r2 > 0.99) with a high precision and good stability (RSD <5%, n = 30) were obtained. Detection limits and reproducibility of the methods have been estimated as ≤0.05 ng L−1 and <5% (0.5 ng L−1, n = 30). The system was finally validated by measurements comparison of the two channels (r2 > 0.98), and analysis of a certified reference material (coastal seawater BCR-579, recoveries 101 ± 4%, n = 10). Overall, a sample throughput of ~10 samples per hour with two-channel detections of FIMA can be achieved. The onboard analysis of inorganic Hg species (e.g. elemental, reactive, and total Hg) in surface seawaters of the East China Sea (ECS) are also successfully achieved. The portable FIMA is fast, easy, and robust for reliable monitoring of Hg in natural seawaters.

Onboard analysis of vehicle emissions in urban ways with different functional classifications

This work seeks to study, through the onboard collection, the emissions of NOX and CO2 pollutants on urban roads with different functional classifications, using otto cycle vehicle. Emissions of vehicle pollutants have been addressed in order to emphasize vehicle dynamics without addressing aspects such as the generation of travel. This work evaluated the influence of functional road classification, urban density, land use, and variation of road loading in vehicle emissions. Real CO2 and NOX emissions were collected and analyzed. The analysis of urban density was not sensitive to compare regions of different degrees of density but provided evidence of vehicle dynamics in the studied roads. In lots of commercial/mixed-use and after signalized intersections, CO2 spikes occurred, stop-and-go events interfered with NOX, however, the variation of this was more sensitive to the time of collection. Peak emissions were observed where the pattern of land use and occupation is mixed, resulting in intense traffic. It is concluded, therefore, that an analysis restricted to vehicle dynamics may not be sufficient to understand the theme of vehicle emissions, as it disregards issues that influence the generation of road trips and, consequently, the emissions profile.

A modified method of on-line solid phase extraction and fluorometric detection for underway monitoring and onboard analysis of trace ammonium in seawater

A sensitive and automated method for underway and onboard analysis of trace ammonium in seawater was established using on-line solid phase extraction and fluorescence detection. Ammonium reacted with o-phthalaldehyde and sulfite to produce isoindole derivative that was concentrated on a hydrophilic lipophilic balanced (HLB) cartridge and then rapidly eluted with ethanol and measured using a fluorescence detector. The work was modified from our previous developed method, where 30 mL of a seawater sample was introduced into a reaction bottle with a 10 mL pipette. In the modified method a 10 mL sample loop was adopted for sample introduction to reduce possible contamination caused by manual operation. More importantly, the present method makes underway monitoring much more automatic. The detection limit was 3.5 nmol L−1, and the relative standard deviation was 3.52% (n = 12) for a sample spiked with 40 nmol L−1 ammonium standard. The method was free of the effects of salinity, carry-over and dissolved organic matter, with recoveries between 94.0% and 106.1%. An equation was introduced to correct matrix effects, and pure water and seawater blank were found to be equivalent to ammonium concentration of 8.1 ± 2.2 nmol L−1 and 6.0 ± 0.8 nmol L−1, respectively. The correction method can also be introduced to determination of other trace analytes where matrix effect cannot be neglected. A technique of stopped-flow was adopted and stopped-flow time could be adjusted depending on the concentration of ammonium in the seawater samples. The sample throughput was 7–9 h−1, and the method permitted the analysis of samples over a wide range of concentrations. The modified method has been successfully applied for shipboard underway determination of ammonium in a coastal area and shipboard determination the ammonium concentration of discrete samples in three vertical profiles during a cruise in the South China Sea.

InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening.

Exploring protein-ligand interactions is a subject of immense interest, as it provides deeper insights into molecular recognition, mechanism of interaction and subsequent functions. Predicting an accurate model for a protein-ligand interaction is a challenging task. Molecular docking is a computational method used for predicting the preferred orientation, binding conformations and the binding affinity of a ligand to a macromolecular target, especially protein. It has been applied in 'virtual high-throughput screening' of chemical libraries containing millions of compounds to find potential leads in drug design and discovery. Here, we have developed InstaDock, a free and open access Graphical User Interface (GUI) program that performs molecular docking and high-throughput virtual screening efficiently. InstaDock is a single-click GUI that uses QuickVina-W, a modified version of AutoDock Vina for docking calculations, made especially for the convenience of non-bioinformaticians and for people who are not experts in using computers. InstaDock facilitates onboard analysis of docking and visual results in just a single click. To sum up, InstaDock is the easiest and more interactive interface than ever existing GUIs for molecular docking and high-throughput virtual screening. InstaDock is freely available for academic and industrial research purposes via https://hassanlab.org/instadock.

Application of an Automatic Analyzer to Onboard Analysis of Nitrate Concentration in a Reductive Fluid

Application of an Automatic Analyzer to Onboard Analysis of Nitrate Concentration in a Reductive Fluid

On-Site Analysis of Bacterial Communities of the Ultraoligotrophic South Pacific Gyre.

The South Pacific Gyre (SPG) covers 10% of the ocean's surface and is often regarded as a marine biological desert. To gain an on-site overview of the remote, ultraoligotrophic microbial community of the SPG, we developed a novel onboard analysis pipeline, which combines next-generation sequencing with fluorescence in situ hybridization and automated cell enumeration. We tested the pipeline during the SO-245 "UltraPac" cruise from Chile to New Zealand and found that the overall microbial community of the SPG was highly similar to those of other oceanic gyres. The SPG was dominated by 20 major bacterial clades, including SAR11, SAR116, the AEGEAN-169 marine group, SAR86, Prochlorococcus, SAR324, SAR406, and SAR202. Most of the bacterial clades showed a strong vertical (20 m to 5,000 m), but only a weak longitudinal (80°W to 160°W), distribution pattern. Surprisingly, in the central gyre, Prochlorococcus, the dominant photosynthetic organism, had only low cellular abundances in the upper waters (20 to 80 m) and was more frequent around the 1% irradiance zone (100 to 150 m). Instead, the surface waters of the central gyre were dominated by the SAR11, SAR86, and SAR116 clades known to harbor light-driven proton pumps. The alphaproteobacterial AEGEAN-169 marine group was particularly abundant in the surface waters of the central gyre, indicating a potentially interesting adaptation to ultraoligotrophic waters and high solar irradiance. In the future, the newly developed community analysis pipeline will allow for on-site insights into a microbial community within 35 h of sampling, which will permit more targeted sampling efforts and hypothesis-driven research.IMPORTANCE The South Pacific Gyre, due to its vast size and remoteness, is one of the least-studied oceanic regions on earth. However, both remote sensing and in situ measurements indicated that the activity of its microbial community contributes significantly to global biogeochemical cycles. Presented here is an unparalleled investigation of the microbial community of the SPG from 20- to 5,000-m depths covering a geographic distance of ∼7,000 km. This insight was achieved through the development of a novel onboard analysis pipeline, which combines next-generation sequencing with fluorescence in situ hybridization and automated cell enumeration. The pipeline is well comparable to onshore systems based on the Illumina platforms and yields microbial community data in less than 35 h after sampling. Going forward, the ability to gain on-site knowledge of a remote microbial community will permit hypothesis-driven research, through the generation of novel scientific questions and subsequent additional targeted sampling efforts.

In situ Determination of Nitrate and Hydrogen Sulfide in the Baltic Sea Using an Ultraviolet Spectrophotometer

Evaluating the health status of marine ecosystems becomes ever increasingly important especially against the backdrop of rising pressures from human activities. This is true especially for coastal seas such as the Baltic Sea that is surrounded by highly industrialized countries. Nutrients and pollutants such as nitrate and hydrogen sulfide, which have a major impact on ecosystem functioning, are two of several key environmental indicators for assessing the status of natural waters, and therefore of considerable interest. The frequency and the spatial coverage of the nitrate and hydrogen sulfide measurements are currently limited by the cost of the laboratory analysis and personnel. Optical in situ sensors can help to overcome this challenge by allowing reagentless and fast detection of dissolved chemical species. A chemical-free optical sensor has been used for direct and simultaneous measurements of both key parameters, and the results were compared with traditional methods. The data were collected during an observational program conducted in the Baltic Sea in February 2018. We used the OPUS UV spectral sensor, which was deployed for the first time in coastal waters, in combination with a deep-sea telemetry system to enable near-real time measurements during CTD profiling. Data processing was carried out using a multiple linear regression procedure. Measurements from both OPUS and on-board analysis were in good agreement. The results showed, that in situ UV-VIS spectrophotometry provides the capability to determine the concentration distributions of nitrate and hydrogen sulfide in the brackish waters of the Baltic Sea.

A pressure core ultrasonic test system for on-board analysis of gas hydrate-bearing sediments under in situ pressures.

The enormous potential as an alternative energy resource has made natural gas hydrates a material of intense research interest. Their exploration and sample characterization require a quick and effective analysis of the hydrate-bearing cores recovered under in situ pressures. Here a novel Pressure Core Ultrasonic Test System (PCUTS) for on-board analysis of sediment cores containing gas hydrates at in situ pressures is presented. The PCUTS is designed to be compatible with an on-board pressure core transfer device and a long gravity-piston pressure-retained corer. It provides several advantages over laboratory core analysis including quick and non-destructive detection, in situ and successive acoustic property acquisition, and remission of sample storage and transportation. The design of the unique assembly units to ensure the in situ detection is demonstrated, involving the U-type protecting jackets, transducer precession device, and pressure stabilization system. The in situ P-wave velocity measurements make the detection of gas hydrate existence in the sediments possible on-board. Performance tests have verified the feasibility and sensitivity of the ultrasonic test unit, showing the dependence of P-wave velocity on gas hydrate saturation. The PCUTS has been successfully applied for analysis of natural samples containing gas hydrates recovered from the South China Sea. It is indicated that on-board P-wave measurements could provide a quick and effective understanding of the hydrate occurrence in natural samples, which can assist further resource exploration, assessment, and subsequent detailed core analysis.