The role of water in APCI-MS online monitoring of gaseous n-alkanes.

In atmospheric pressure chemical ionization mass spectrometry (APCI-MS), [M-3H+H2O]+ ions can deliver analyte-specific signals that enable direct analysis of volatile n-alkane mixtures. The underlying ionization mechanisms have been the subject of open debate, and in particular the role of water is insufficiently clarified to allow for reliable process analytics when the humidity level changes over time. This can be a problem, particularly in online monitoring, where analyte accumulation in the ion source can also occur. Here, we investigated the role of water during APCI-MS of volatile n-alkanes by changing the carrier gas for sample injection from a dry to a wetted state as well as by using 18O-labeled water. This allowed for a distinction between gaseous and surface-adsorbed water molecules. While adsorbed water seems to be responsible for the desired [M-3H+H2O]+ signals through surface reactions with the analyte molecules, gaseous water was found to promote the formation of CnH2n+1O+ of different (and analyte-independent) hydrocarbons, revealing a reaction with hydrocarbon species which accumulated in the ion source during continuous operation. At the same time, gaseous water competed with analyte molecules for ionization and thus suppressed the formation of alkyl (CnH2n+1+) and alkenyl (CnH2n-1+) ions. The results reveal a memory effect due to hydrocarbon adsorption, which may cause severe interpretation difficulties when the ionization chamber undergoes sudden humidity changes. The use of [M-3H+H2O]+ for n-alkane analysis in alkane/water mixtures can be facilitated by constantly maintaining high humidity and hence stabilizing the ionization conditions.

Rapid online analysis of n-alkanes in gaseous streams via APCI mass spectrometry.

Online monitoring of dynamic chemical processes involving a wide volatility range of hydrocarbon species is challenging due to long chromatographic measurement times. Mass spectrometry (MS) overcomes chromatographic delays. However, the analysis of n-alkane mixtures by MS is difficult because many fragment ions are formed, which leads to overlapping signals of the homologous series. Atmospheric pressure chemical ionization (APCI) is suitable for the analysis of saturated hydrocarbons and is the subject of current research. Still, although APCI is a "soft ionization" technique, fragmentation is typically inevitable. Moreover, it is usually applied for liquid samples, while an application for online gas-phase monitoring is widely unexplored. Here, we present an automated APCI-MS method for an online gas-phase analysis of volatile and semi-volatile n-alkanes. Mass spectra for n-heptane and n-decane reveal [M-H]+, [M-3H]+ and [M-3H+H2O]+ as abundant ions. While [M-H]+ and [M-3H]+ show an excessive fragmentation pattern to smaller CnH2n+1+ and CnH2n-1+ cations, [M-3H+H2O]+ is the only relevant signal within the CnH2n+1O+ ion group, i.e., no chain cleavage is observed. This makes [M-3H+H2O]+ an analyte-specific ion that is suitable for the quantification of n-alkane mixtures. A calibration confirms the linearity of C7 and C10 signals up to concentrations of ~1000-1500 ppm. Moreover, validated concentration profiles are measured for a binary C7/C10 mixture and a five-alkane C7/C10/C12/C14/C20 mixture. Compared to the 40-min sampling interval of the reference gas chromatograph, MS sampling is performed within 5 min and allows dynamic changes to be monitored.

A Method for the Pattern Recognition of Acoustic Emission Signals Using Blind Source Separation and a CNN for Online Corrosion Monitoring in Pipelines with Interference from Flow-Induced Noise.

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert-Huang transform (HHT) was applied to each source signal to obtain a joint time-frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%.

Research on Online Monitoring Technology and Filtration Process of Inclusions in Aluminum Melt.

Online monitoring and real-time feedback on inclusions in molten metal are essential for metal quality control. However, existing methods for detecting aluminum melt inclusions face challenges, including interference, prolonged processing times, and latency. This paper presents the design and development of an online monitoring system for molten metal inclusions. Initially, the system facilitates real-time adjustment of signal acquisition parameters through a multiplexer. Subsequently, it employs a detection algorithm capable of swiftly extracting pulse peaks, with this task integrated into our proprietary host computer software to ensure timely detection and data visualization. Ultimately, we developed a monitoring device integrated with this online monitoring system, enabling the online monitoring of the aluminum alloy filtration process. Our findings indicate that the system can accurately measure the size and concentration of inclusions during the filtration process in real time, offering enhanced detection speed and stability compared to the industrial LiMCA CM (liquid metal cleanliness analyzer continuous monitoring) standard. Furthermore, our evaluation of the filtration process demonstrates that the effectiveness of filtration significantly improves with the increase in inclusion sizes, and the synergistic effect of combining CFF (ceramic foam filter) and MCF (metallics cartridge filter) filtration methods exceeds the performance of the CFF method alone. This system thus provides valuable technical support for optimizing filtration processes and controlling inclusion quality.

Development of a Microwave Sensor for Real-Time Monitoring of a Micro Direct Methanol Fuel Cell.

Micro direct methanol fuel cells (µDMFCs) are a promising power source for microelectronic devices and systems. As the operating state and performance of a µDMFC is generally determined by both electrochemical polarization and methanol crossover, it is important to monitor the methanol concentration in µDMFCs. Here, we design and fabricate a microwave sensor and integrate it with a µDMFC for the online detection of methanol concentration in a nonintrusive way. The sensing area is set at the bottom of the anode chamber of a µDMFC which exhibits a maximum output power density of 28.8 mW cm-2 at 30 °C. With a square ring structure, the dual-mode microwave sensor shows a sensitivity of 9.5 MHz mol-1 L. Furthermore, the importance of methanol concentration monitoring is demonstrated in the long term. A relatively smooth methanol decline curve was obtained, which indicated a normal and stable operating status of the µDMFC. Derived from real-time recording data, fuel utilization was additionally calculated as 28.5%.

A "Prediction - Detection - Judgment" framework for sudden water contamination event detection with online monitoring.

The contamination detection technology helps in water quality management and protection in surface water. It is important to detect sudden contamination events timely from dynamic variations due to various interference factors in online water quality monitoring data. In this study, a framework named "Prediction - Detection - Judgment" is proposed with a method framework of "Time series increment - Hierarchical clustering - Bayes' theorem model". Time to detection is used as an evaluation index of contamination detection methods, along with the probability of detection and false alarm rate. The proposed method is tested with available public data and further applied in a monitoring site of a river. Results showed that the method could detect the contamination events with a 100% probability of detection, a 17% false alarm rate and a time to detection close to 4 monitoring intervals. The proposed index time to detection evaluates the timeliness of the method, and timely detection ensures that contamination events can be responded to and dealt with in time. The site application also demonstrates the feasibility and practicability of the framework proposed in this study and its potential for extensive implementation.

Real-time detection of mean and variance changes in experience sampling data: A comparison of existing and novel statistical process control approaches.

Retrospective analyses of experience sampling (ESM) data have shown that changes in mean and variance levels may serve as early warning signs of an imminent depression. Detecting such early warning signs prospectively would pave the way for timely intervention and prevention. The exponentially weighted moving average (EWMA) procedure seems a promising method to scan ESM data for the presence of mean changes in real-time. Based on simulation and empirical studies, computing and monitoring day averages using EWMA works particularly well. We therefore expand this idea to the detection of variance changes and propose to use EWMA to prospectively scan for mean changes in day variability statistics (i.e., s 2 , s , ln( s )). When both mean and variance changes are of interest, the multivariate extension of EWMA (MEWMA) can be applied to both the day averages and a day statistic of variability. We evaluate these novel approaches to detecting variance changes by comparing them to EWMA-type procedures that have been specifically developed to detect a combination of mean and variance changes in the raw data: EWMA- S 2 , EWMA-ln( S 2 ), and EWMA- X ¯ - S 2 . We ran a simulation study to examine the performance of the two approaches in detecting mean, variance, or both types of changes. The results indicate that monitoring day statistics using (M)EWMA works well and outperforms EWMA- S 2 and EWMA-ln( S 2 ); the performance difference with EWMA- X ¯ - S 2 is smaller but notable. Based on the results, we provide recommendations on which statistic of variability to monitor based on the type of change (i.e., variance increase or decrease) one expects.

A novel mathematical template for developing fDOM probe fluorescence signal correction models for freshwaters.

The reliable application of field deployable fluorescent dissolved organic matter (fDOM) probes is hindered by several influencing factors which need to be compensated. This manuscript describes the corrections of temperature, pH, turbidity and inner filter effect on fluorescence signal of a commercial fDOM probe (fDOMs). For this, Australian waters with wide ranging qualities were selected, e.g. dissolved organic carbon (DOC) ranging from ∼1 to ∼30 mg/L, specific UV absorbance at 254 nm from ∼1 to ∼6 L/m/mg and turbidity from ∼1 to ∼ 350 FNU. Laboratory-based model calibration experiments (MCEs) were performed. A model template was developed and used for the development of the correction models. For each factor, data generated through MCEs were used to determine model coefficient (α) values by fitting the generated model to the experimental data. Four discrete factor models were generated by determination of a factor-specific α value. The α values derived for each water of the MCEs subset were consistent for each factor model. This indicated generic nature of the four α values across wide-ranging water qualities. High correlation between fDOMs and DOC were achieved after applying the four-factor compensation models to new data (r, 0.96, p < 0.05). Also, average biases (and %) between DOC predicted through fDOMs and actual DOC were decreased by applying the four-factor compensation model (from 3.54 (60.9%) to 1.28 (16.7%) mg/L DOC). These correction models were incorporated into a Microsoft EXCEL-based software termed EXOf-Correct for ready-to-use applications.

[Application of process analysis technology in traditional Chinese medicine manufacturing industry].

In the traditional Chinese medicine(TCM) manufacturing industry, quality control determines the safety, effectiveness, and quality stability of the final product. The traditional quality control method generally carries out sampling off-line testing of drugs after the end of the batch production, which is incomprehensive, and it fails to find the problems in the production process in time. Process analysis technology(PAT) uses process testing, mathematical modeling, data analysis, and other technologies to collect, analyze, feedback, control, and continuously improve the critical quality attributes(CQA) in all aspects of the production of TCM preparations in real time. The application of PAT in the TCM manufacturing industry is one of the research hotspots in recent years, which has the advantages of real-time, systematic, non-destructive, green, and rapid detection for the production quality control of TCM preparations. It can effectively ensure the stability of the quality of TCM preparations, improve production efficiency, and play a key role in the study of the quantity and quality transfer law of TCM. Commonly used PAT includes near-infrared spectroscopy, Raman spectroscopy, online microwave, etc. In addition, the establishment of an online detection model by PAT is the key basic work to realize intelligent manufacturing in TCM production. Obtaining real-time online detection data through PAT and establishing a closed-loop control model on this basis are a key common technical difficulty in the industry. This paper adopted systematic literature analysis to summarize the relevant Chinese and foreign literature, policies and regulations, and production applications, and it introduced the development trend and practical application of PAT, so as to provide references for accelerating the application of PAT in the TCM manufacturing industry, the intelligent transformation and upgrading, and high-quality development of the TCM industry.

Development of a chemically defined medium for Paenibacillus polymyxa by parallel online monitoring of the respiration activity in microtiter plates.

BACKGROUND: One critical parameter in microbial cultivations is the composition of the cultivation medium. Nowadays, the application of chemically defined media increases, due to a more defined and reproducible fermentation performance than in complex media. In order, to improve cost-effectiveness of fermentation processes using chemically defined media, the media should not contain nutrients in large excess. Additionally, to obtain high product yields, the nutrient concentrations should not be limiting. Therefore, efficient medium optimization techniques are required which adapt medium compositions to the specific nutrient requirements of microorganisms. RESULTS: Since most Paenibacillus cultivation protocols so far described in literature are based on complex ingredients, in this study, a chemically defined medium for an industrially relevant Paenibacillus polymyxa strain was developed. A recently reported method, which combines a systematic experimental procedure in combination with online monitoring of the respiration activity, was applied and extended to identify growth limitations for Paenibacillus polymyxa. All cultivations were performed in microtiter plates. By systematically increasing the concentrations of different nutrient groups, nicotinic acid was identified as a growth-limiting component. Additionally, an insufficient buffer capacity was observed. After optimizing the growth in the chemically defined medium, the medium components were systematically reduced to contain only nutrients relevant for growth. Vitamins were reduced to nicotinic acid and biotin, and amino acids to methionine, histidine, proline, arginine, and glutamate. Nucleobases/-sides could be completely left out of the medium. Finally, the cultivation in the reduced medium was reproduced in a laboratory fermenter. CONCLUSION: In this study, a reliable and time-efficient high-throughput methodology was extended to investigate limitations in chemically defined media. The interpretation of online measured respiration activities agreed well with the growth performance of samples measured in parallel via offline analyses. Furthermore, the cultivation in microtiter plates was validated in a laboratory fermenter. The results underline the benefits of online monitoring of the respiration activity already in the early stages of process development, to avoid limitations of medium components, oxygen limitation and pH inhibition during the scale-up.

Black glucose-releasing silicon elastomer rings for fed-batch operation allow measurement of the oxygen transfer rate from the top and optical signals from the bottom for each well of a microtiter plate.

BACKGROUND: In industrial microbial biotechnology, fed-batch processes are frequently used to avoid undesirable biological phenomena, such as substrate inhibition or overflow metabolism. For targeted process development, fed-batch options for small scale and high throughput are needed. One commercially available fed-batch fermentation system is the FeedPlate®, a microtiter plate (MTP) with a polymer-based controlled release system. Despite standardisation and easy incorporation into existing MTP handling systems, FeedPlates® cannot be used with online monitoring systems that measure optically through the transparent bottom of the plate. One such system that is broadly used in biotechnological laboratories, is the commercial BioLector. To allow for BioLector measurements, while applying the polymer-based feeding technology, positioning of polymer rings instead of polymer disks at the bottom of the well has been proposed. This strategy has a drawback: measurement requires an adjustment of the software settings of the BioLector device. This adjustment modifies the measuring position relative to the wells, so that the light path is no longer blocked by the polymer ring, but, traverses through the inner hole of the ring. This study aimed at overcoming that obstacle and allowing for measurement of fed-batch cultivations using a commercial BioLector without adjustment of the relative measurement position within each well. RESULTS: Different polymer ring heights, colours and positions in the wells were investigated for their influence on maximum oxygen transfer capacity, mixing time and scattered light measurement. Several configurations of black polymer rings were identified that allow measurement in an unmodified, commercial BioLector, comparable to wells without rings. Fed-batch experiments with black polymer rings with two model organisms, E. coli and H. polymorpha, were conducted. The identified ring configurations allowed for successful cultivations, measuring the oxygen transfer rate and dissolved oxygen tension, pH, scattered light and fluorescence. Using the obtained online data, glucose release rates of 0.36 to 0.44 mg/h could be determined. They are comparable to formerly published data of the polymer matrix. CONCLUSION: The final ring configurations allow for measurements of microbial fed-batch cultivations using a commercial BioLector without requiring adjustments of the instrumental measurement setup. Different ring configurations achieve similar glucose release rates. Measurements from above and below the plate are possible and comparable to measurements of wells without polymer rings. This technology enables the generation of a comprehensive process understanding and target-oriented process development for industrial fed-batch processes.

Spotting priming-active compounds using parsley cell cultures in microtiter plates.

BACKGROUND: Conventional crop protection has major drawbacks, such as developing pest and pathogen insensitivity to pesticides and low environmental compatibility. Therefore, alternative crop protection strategies are needed. One promising approach treats crops with chemical compounds that induce the primed state of enhanced defense. However, identifying priming compounds is often tedious as it requires offline sampling and analysis. High throughput screening methods for the analysis of priming-active compounds have great potential to simplify the search for such compounds. One established method to identify priming makes use of parsley cell cultures. This method relies on measurement of fluorescence of furanocoumarins in the final sample. This study demonstrates for the first time the online measurement of furanocoumarins in microtiter plates. As not all plants produce fluorescence molecules as immune response, a signal, which is not restricted to a specific plant is required, to extend online screening methods to other plant cell cultures. It was shown that the breathing activity of primed parsley cell cultures increases, compared to unprimed parsley cell cultures. The breathing activity can by monitored online. Therefore, online identification of priming-inducing compounds by recording breathing activity represents a promising, straight-forward and highly informative approach. However, so far breathing has been recorded in shake flasks which suffer from low throughput. For industrial application we here report a high-throughput, online identification method for identifying priming-inducing chemistry. RESULTS: This study describes the development of a high-throughput screening system that enables identifying and analyzing the impact of defense priming-inducing compounds in microtiter plates. This screening system relies on the breathing activity of parsley cell cultures. The validity of measuring the breathing activity in microtiter plates to drawing conclusions regarding priming-inducing activity was demonstrated. Furthermore, for the first time, the fluorescence of the priming-active reference compound salicylic acid and of furanocoumarins were simultaneously monitored online. Dose and time studies with salicylic acid-treated parsley cell suspensions revealed a wide range of possible addition times and concentrations that cause priming. The online fluorescence measuring method was further confirmed with three additional compounds with known priming-causing activity. CONCLUSIONS: Determining the OTR, fluorescence of the priming-active chemical compound SA and of furanocoumarins in parsley suspension cultures in MTPs by online measurement is a powerful and high-throughput tool to study possible priming compounds. It allows an in-depth screening for priming compounds and a better understanding of the priming process induced by a given substance. Evaluation of priming phenomena via OTR should also be applicable to cell suspensions of other plant species and varieties and allow screening for priming-inducing chemical compounds in intact plants. These online fluorescence methods to measure the breathing activity, furanocoumarin and SA have the potential to accelerate the search for new priming compounds and promote priming as a promising, eco-friendly crop protection strategy.

Continuous monitoring of IgG using immobilized fluorescent reporters.

In the manufacture of therapeutic monoclonal antibodies, the clarified cell culture fluid (CCF) is typically loaded onto an initial protein A affinity capture column. Imperfect mass transfer and loading to maximum capacity can risk antibody breakthrough and loss of valuable product, but conservative underloading wastes expensive protein A resin. In addition, the effects of column fouling and ligand degradation require the frequent optimization of immunoglobulin G (IgG) loading to avoid wastage. Continuous real-time monitoring of IgG flowthrough is of great interest, therefore. We previously developed a fluorescence-based monitoring technology that allows batch mix-and-read mAb detection in the CCF. Here, we report the use of reporters immobilized on cyanogenbromide-activated Sepharose 4B resin for continuous detection of IgG in column breakthrough. The column effluent is continuously contacted with immobilized fluorescein-labeled Fc-binding ligands in a small monitoring column to produce an immediately-detectable change in fluorescence intensity. The technology allows rapid and reliable monitoring of IgG in a flowing stream of clarified CCF emerging from a protein A column, without prior sample preparation. We observed a significant change in fluorescence intensity at 0.5 g/L human IgG, sufficient to detect a 5% breakthrough of a 10 g/L load, within 18 s at a flow rate of 0.5 ml/min. The current small-scale technology is suitable for use in process development, but the chemistry should be readily adaptable to larger scale applications using fiber-optic sensors, and continuous IgG monitoring could be applicable in a variety of upstream and downstream process settings.

Advancing 2D fluorescence online monitoring in microtiter plates by separating scattered light and fluorescence measurement, using a tunable emission monochromator.

Online fluorescence monitoring has become a key technology in modern bioprocess development, as it provides in-depth process knowledge at comparably low costs. In particular, the technology is widely established for high-throughput microbioreactor cultivation systems, due to its noninvasive character. For microtiter plates, previously also multi-wavelength 2D fluorescence monitoring was developed. To overcome an observed limitation of fluorescence sensitivity, this study presents a modified spectroscopic setup, including a tunable emission monochromator. The new optical component enables the separation of the scattered and fluorescent light measurements, which allows for the adjustment of integration times of the charge-coupled device detector. The resulting increased fluorescence sensitivity positively affected the performance of principal component analysis for spectral data of Escherichia coli batch cultivation experiments with varying sorbitol concentration supplementation. In direct comparison with spectral data recorded at short integration times, more biologically consistent signal dynamics were calculated. Furthermore, during partial least square regression for E. coli cultivation experiments with varying glucose concentrations, improved modeling performance was observed. Especially, for the growth-uncoupled acetate concentration, a considerable improvement of the root-mean-square error from 0.25 to 0.17 g/L was achieved. In conclusion, the modified setup represents another important step in advancing 2D fluorescence monitoring in microtiter plates.

Hydrogen online monitoring based on thermal conductivity for anaerobic microorganisms.

H2 -producing microorganisms are a promising source of sustainable biohydrogen. However, most H2 -producing microorganisms are anaerobes, which are difficult to cultivate and characterize. While several methods for measuring H2 exist, common H2 sensors often require oxygen, making them unsuitable for anaerobic processes. Other sensors can often not be operated at high gas humidity. Thus, we applied thermal conductivity (TC) sensors and developed a parallelized, online H2 monitoring for time-efficient characterization of H2 production by anaerobes. Since TC sensors are nonspecific for H2 , the cross-sensitivity of the sensors was evaluated regarding temperature, gas humidity, and CO2 concentrations. The systems' measurement range was validated with two anaerobes: a high H2 -producer (Clostridium pasteurianum) and a low H2 -producer (Phocaeicola vulgatus). Online monitoring of H2 production in shake flask cultivations was demonstrated, and H2 transfer rates were derived. Combined with online CO2 and pressure measurements, molar gas balances of the cultivations were closed, and an anaerobic respiration quotient was calculated. Thus, insight into the effect of medium components and inhibitory cultivation conditions on H2 production with the model anaerobes was gained. The presented online H2 monitoring method can accelerate the characterization of anaerobes for biohydrogen production and reveal metabolic changes without expensive equipment and offline analysis.

Yeast extracts from different manufacturers and supplementation of amino acids and micro elements reveal a remarkable impact on alginate production by A. vinelandii ATCC9046.

BACKGROUND: In research and production, reproducibility is a key factor, to meet high quality and safety standards and maintain productivity. For microbial fermentations, complex substrates and media components are often used. The complex media components can vary in composition, depending on the lot and manufacturing process. These variations can have an immense impact on the results of biological cultivations. The aim of this work was to investigate and characterize the influence of the complex media component yeast extract on cultivations of Azotobacter vinelandii under microaerobic conditions. Under these conditions, the organism produces the biopolymer alginate. The focus of the investigation was on the respiration activity, cell growth and alginate production. RESULTS: Yeast extracts from 6 different manufacturers and 2 different lots from one manufacturer were evaluated. Significant differences on respiratory activity, growth and production were observed. Concentration variations of three different yeast extracts showed that the performance of poorly performing yeast extracts can be improved by simply increasing their concentration. On the other hand, the results with well-performing yeast extracts seem to reach a saturation, when their concentration is increased. Cultivations with poorly performing yeast extract were supplemented with grouped amino acids, single amino acids and micro elements. Beneficial results were obtained with the supplementation of copper sulphate, cysteine or a combination of both. Furthermore, a correlation between the accumulated oxygen transfer and the final viscosity (as a key performance indicator), was established. CONCLUSION: The choice of yeast extract is crucial for A. vinelandii cultivations, to maintain reproducibility and comparability between cultivations. The proper use of specific yeast extracts allows the cultivation results to be specifically optimised. In addition, supplements can be applied to modify and improve the properties of the alginate. The results only scratch the surface of the underlying mechanisms, as they are not providing explanations on a molecular level. However, the findings show the potential of optimising media containing yeast extract for alginate production with A. vinelandii, as well as the potential of targeted supplementation of the media.

Real-Time and Online Monitoring of Hazardous Volatile Organic Compounds in Environmental Water by an Unmanned Shipborne Mass Spectrometer System.

Hazardous volatile organic compounds (VOCs) are one of the critical concerns in environmental water due to their toxicity to aquatic organisms and drinking water. Therefore, rapid detection of hazardous VOCs in environmental water is highly needed as many analytical methods are limited to on-site monitoring. In this work, we designed a novel unmanned shipborne mass spectrometer (US-MS) system for the real-time and online monitoring of hazardous VOCs in environmental water. The US-MS system consists of a miniaturized mass spectrometer, an automatic sampling device, a robust unmanned ship, and other monitoring and control devices. Along with the navigation route of the US-MS system, environmental water was continuously introduced into the MS system for the online and real-time detection of hazardous VOCs via a liquid/gas exchange membrane. Analytical performances of the US-MS system were investigated by a mixture of 10 VOCs showing low limits of detection (LODs: 0.31-1.26 ng/mL), good reproducibility (RSDs: 2.93-11.03%, n = 7), and excellent quantitative ability (R2 > 0.99). Furthermore, on-site detection and online monitoring of hazardous volatile contaminants such as benzene, chloroprene, and toluene in different aquatic environments such as rivers and lakes were successfully demonstrated, showing excellent field applicability of the US-MS system. Overall, the newly developed US-MS system could perform on-site, online, and real-time monitoring of complex VOCs in environmental water, showing good performances and versatile applications in water analysis.

Effects of reducing, stabilizing, and antibiotic agents on "Candidatus Kuenenia stuttgartiensis".

Anaerobic ammon ium oxidizing (anammox) bacteria oxidize ammonium and reduce nitrite, producing N2, and could play a major role in energy-optimized wastewater treatment. However, sensitivity to various environmental conditions and slow growth currently hinder their wide application. Here, we attempted to determine online the effect of environmental stresses on anammox bacteria by using an overnight batch activity test with whole cells, in which anammox activity was calculated by quantifying N2 production via headspace-pressure monitoring. A planktonic mixed culture dominated by "Candidatus Kuenenia stuttgartiensis" strain CSTR1 was cultivated in a 30-L semi-continuous stirring tank reactor. In overnight resting-cell anammox activity tests, oxygen caused strong inhibition of anammox activity, which was reversed by sodium sulfite (30 µM). The tested antibiotics sulfamethoxazole, kanamycin, and ciprofloxacin elicited their effect on a dose-dependent manner; however, strain CSTR1 was highly resistant to sulfamethoxazole. Anammox activity was improved by activated carbon and Fe2O3. Protein expression analysis from resting cells after anammox activity stimulation revealed that NapC/NirT family cytochrome c (KsCSTR_12840), hydrazine synthase, hydrazine dehydrogenase, hydroxylamine oxidase, and nitrate:nitrite oxidoreductase were upregulated, while a putative hydroxylamine oxidoreductase HAO (KsCSTR_49490) was downregulated. These findings contribute to the growing knowledge on anammox bacteria physiology, eventually leading to the control of anammox bacteria growth and activity in real-world application. KEY POINTS: • Sulfite additions can reverse oxygen inhibition of the anammox process • Anammox activity was improved by activated carbon and ferric oxide • Sulfamethoxazole marginally affected anammox activity.

Development of Innovative Online Modularized Device for Turbidity Monitoring.

Given progress in water-quality analytical technology and the emergence of the Internet of Things (IoT) in recent years, compact and durable automated water-quality monitoring devices have substantial market potential. Due to susceptibility to the influence of interfering substances, which lowers measurement accuracy, existing automated online monitoring devices for turbidity, a key indicator of a natural water body, feature a single light source and are thus insufficient for more complicated water-quality measurement. The newly developed modularized water-quality monitoring device boasts dual light sources (VIS/NIR), capable of measuring the intensity of scattering, transmission, and reference light at the same time. Coupled with a water-quality prediction model, it can attain a good estimate for continuing monitoring of tap water (<2 NTU, error < 0.16 NTU, relative error < 19.6%) and environmental water samples (<400 NTU, error < 3.86 NTU, relative error < 2.3%). This indicates the optical module can both monitor water quality in low turbidity and provide water-treatment information alerts in high turbidity, thereby materializing automated water-quality monitoring.

Design of Twin Builder-Based Digital Twin Online Monitoring System for Crane Girders.

The crossbeam is frequently subjected to alternating loads during work as an essential load-bearing part of the crane. However, due to the large volume and the limitations of detection technology, it is impossible to realize online monitoring of the mechanical state. The ongoing advancement of ROMing and digital twin technology plays a pivotal role in facilitating the resolution of this particular issue. In this paper, we take the crane beam as the physical entity and combine the Twin Builder reduced-order technology and Deployer digital twin deployment technology to establish a digital twin of the beam. The load recognition model within the twin system exhibits a prediction error rate of ±5%. Furthermore, the accuracy of the ROM surpasses that of conventional machine learning models by a factor of 25. Upon deployment on the web platform, the results are delivered within 0.5 s, representing a substantial improvement as it is merely 1/15 of the time required for traditional 3D displays. The digital twin online monitoring system has the advantages of high accuracy and low requirements for monitoring equipment, which can be widely used in engineering practice to solve the problem that the mechanical state of large parts cannot be accurately monitored online.