Search Results (21)

With the rise of industry, river pollution has become increasingly severe. Countries worldwide now face the challenge of effectively and promptly detecting river pollution. Traditional river detection methods rely on manual sampling and subsequent data analysis at various sampling sites, requiring significant time and labor costs. This article proposes using an electric unmanned surface vehicle (USV) to replace manual river and lake water quality detection, utilizing a 2.4 G high-power wireless data transmission system, an M9N GPS antenna, and an automatic identification system (AIS) to achieve remote and unmanned control. The USV is capable of autonomously navigating along pre-defined routes and conducting water quality measurements without human intervention. The water quality detection system includes sensors for pH, dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP). This design uses a modular structure, it is easy to maintain, and it supports long-range wireless communication. These features help to reduce operational and maintenance costs in the long term. The data produced using this method effectively reflect the current state of river water quality and indicate whether pollution is present. Through practical testing, this article demonstrates that the USV can perform precise positioning while utilizing AIS to identify potential surrounding collision risks for the remote planning of water quality detection sailing routes. This autonomous approach enhances the efficiency of water sampling in rivers and lakes and significantly reduces labor requirements. At the same time, this contributes to the achievement of the United Nations Sustainable Development Goals (SDG 14), “Life Below Water”. Full article

The study addresses the critical issue of accurately predicting ammonia nitrogen (NH₃-N) concentration in a sequencing batch reactor (SBR) system, achieving reduced consumption through automatic control technology. NH₃-N concentration serves as a key indicator of treatment efficiency and environmental impact; however, its complex dynamics and the scarcity of measurements pose significant challenges for accurate prediction. To tackle this problem, an innovative Transformer-long short-term memory (Transformer-LSTM) network model was proposed, which effectively integrates the strengths of both Transformer and LSTM architectures. The Transformer component excels at capturing long-range dependencies, while the LSTM component is adept at modeling sequential patterns. The innovation of the proposed methodology resides in the incorporation of dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP) as input variables, along with their respective rate of change and cumulative value. This strategic selection of input features enhances the traditional utilization of water quality indicators and offers a more comprehensive dataset for prediction, ultimately improving model accuracy and reliability. Experimental validation on NH₃-N datasets from the SBR system reveals that the proposed model significantly outperforms existing advanced methods in terms of root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R²). Furthermore, by integrating real-time sensor data with the Transformer-LSTM network and automatic control, substantial improvements in water treatment processes were achieved, resulting in a 26.9% reduction in energy or time consumption compared with traditional fixed processing cycles. This methodology provides an accurate and reliable tool for predicting NH₃-N concentrations, contributing significantly to the sustainability of water treatment and ensuring compliance with emission standards. Full article

Mitoregulin (MTLN) is a 56-amino-acid mitochondrial microprotein known to modulate mitochondrial energetics. MTLN gene expression is elevated broadly across most cancers and has been proposed as a prognostic biomarker for non-small cell lung cancer (NSCLC). In addition, lower MTLN expression in lung adenocarcinoma (LUAD) correlates with significantly improved patient survival. In our studies, we have found that MTLN silencing in A549 NSCLC cells slowed proliferation and, in accordance with this, we observed the following: (1) increased proportion of cells in the G1 phase of cell cycle; (2) protein changes consistent with G1 arrest (e.g., reduced levels and/or reduced phosphorylation of ERK, MYC, CDK2, and RB, and elevated p27^Kip1); (3) reduction in clonogenic cell survival and; (4) lower steady-state cytosolic and mitochondrial H₂O₂ levels as indicated by use of the roGFP2-Orp1 redox sensor. Conflicting with G1 arrest, we observed a boost in cyclin D1 abundance. We also tested MTLN silencing in combination with buthionine sulfoximine (BSO) and auranofin (AF), drugs that inhibit GSH synthesis and thioredoxin reductase, respectively, to elevate the reactive oxygen species (ROS) amount to a toxic range. Interestingly, clonogenic survival after drug treatment was greater for MTLN-silenced cultures versus the control cultures. Lower H₂O₂ output and reduced vulnerability to ROS damage due to G1 status may have jointly contributed to the partial BSO + AF resistance. Overall, our results provide evidence that MTLN fosters H₂O₂ signaling to propel G1/S transition and suggest MTLN silencing as a therapeutic strategy to limit NSCLC growth. Full article

Recirculating aquaculture system (RAS) technology is seen worldwide as a solution for sustainable fish production. However, there are still deficiencies in the process technology imperiling consistent operation and thus economic results. Drawbacks are linked to essential processes of the water treatment systems such as denitrification. Nitrogenous waste needs to be removed from RAS process water to maintain an adequate production environment for fish and to mitigate the environmental impact of discharged process water. At present, denitrification lacks reliable process control, especially regarding the organic carbon feed to heterotrophic denitrification processes. An investigation into heterotrophic denitrification in an experimental RAS resulted in the discovery of a virtual sensor based on measurements of the oxidation reduction potential (ORP). The virtual sensor responds to an insufficient carbon feed to denitrification. It is based on the oxidation of nitrite in an ozone-enhanced foam flotation installed downstream of the denitrification. The sensor essentially delivers a binary signal denoting either a complete or an incomplete denitrification process. The virtual sensor can be used for reliably controlling heterotrophic denitrification. It requires an upgraded process chain employing ozone-enhanced foam flotation (protein skimmer) downstream of the denitrification. However, the virtual sensor does not require any additional instrumentation. Full article

Phytoremediation is used to treat wastewater, wherein plants, microorganisms, and soil work together to remediate pollutants. We evaluated the plant processes that can affect metal mobilization during phytoremediation. The experimental columns were filled with silica sand and soil mixture spiked with redox-sensitive metal(loid)s—arsenic, manganese, and iron, and fitted with an ORP probe and oxygen sensors. Three columns were planted with poplars and three others were no-plant controls. Carbon-rich, synthetic food-processing wastewater was applied at 15.4 mm/day to the columns. Leachate water was analyzed every other week for water quality. Both soil and plant tissue samples were analyzed for metal concentrations, and soils were analyzed for microbial populations. Both treatments reduced 65–70% carbon. ORP ranged from −321 mV to 916 mV and affected metal mobilization. Oxic conditions in planted treatments yielded high ORP, oxygen concentration, and nitrates. Microbial communities were enhanced in both treatments, but the planted columns had more microbial abundance and evenness. Plants successfully accumulated metals in roots from soil with an accumulation factor of up to 40 for some metals and translocated to shoots from roots with a translocation factor of 10.62. The crop coefficient was 1.88, indicating accelerated loss of water in planted columns compared to control columns. The results demonstrated the benefits of plants in creating more oxic conditions, removing more wastewater from the rhizosphere, accumulating and translocating metals in the biomass, and enhancing rhizodegradation of pollutants by microbial population enhancement. Knowledge of the soil–plant–microbial processes is useful in designing engineered phytoremediation systems. Full article

With the consumption of terrestrial metal resources, deep-sea polymetallic nodule minerals have been widely exploited around the world. Therefore, the environmental impact of deep-sea polymetallic nodule mining cannot be ignored. In this study, for the first time, a field disturbance and observation device, integrated with multiple sensors, is used to simulate the disturbance process of mining on seabed sediments in the polymetallic nodule area of the western Pacific Ocean at a depth of 5700 m. The impact of the process of stroking and lifting on the bottom sediment in the polymetallic nodule area is 30 times higher than that caused by the waves or the current. The time for turbidity to return to normal after the increase is about 30 min, and the influence distance of a disturbance to the bottom bed on turbidity is about 126 m. The time it takes for density to return to normal is about four hours, and the influence is about 1000 m. At the same time, the resuspension of the bottom sediment leads to an increase in density anomaly and salinity. Moreover, suspended sediments rich in metal ions may react with dissolved oxygen in water, resulting in a decrease in the dissolved oxygen content and an increase in ORP. During the observation period, the phenomenon of a deep-sea reciprocating current is found, which may cause the suspended sediment generated by the continuous operation of the mining vehicle to produce suspended sediment clouds in the water near the bottom of the mining area. This could lead to the continuous increase in nutrients in the water near the bottom of the mining area and the continuous reduction in dissolved oxygen, which will have a significant impact on the local ecological environment. Therefore, the way mining vehicles dig and wash in water bodies could have a marked impact on the marine environment. We suggest adopting the technology of suction and ore separation on mining ships, as well as bringing the separated sediment back to the land for comprehensive utilization. Full article

Machine-learning-based models are used to predict dissolved oxygen (DO); however, acquiring continuous water quality data for input variables in harsh environments remains challenging. Herein, redox potential (ORP) determined by a thermo-treated flexible carbon fiber electrode was introduced as a single or preferential input variable for machine-learning-based DO prediction in a year-round eutrophic estuary. The novel ORP sensor was operated for 4 months, and DO was predicted from ORP and six water quality data sources using a long short-term memory (LSTM) neural network. ORP and DO concentration showed a linear correlation, but the first-order correlation slopes varied seasonally. The optimal LSTM hyperparameters were proposed, which depended on the prediction time step and predictor case. Simulation results showed higher seasonal DO dynamics reproduced using ORP alone (RMSE = 1.09) than that predicted using six other water quality parameters (RMSE = 1.32). In addition, ORP played a key role in DO prediction when combined with all water quality parameters (RMSE = 1.08). The feature importance of ORP as a predictor was evaluated from a random forest model. Overall, the highly selective redox sensor has a distinct response to DO concentration and offers a novel and cost-effective approach for monitoring or predicting DO in eutrophic waters. Full article

Water is an essential element for every plant to survive, absorb nutrients, and perform photosynthesis and respiration. If water is polluted, plant growth can be truncated. The aim of this research is to develop a water quality monitoring system for agriculture purposes based on integration of sensing framework with a smart decision support method. This research consists of three stages: (1) the first stage: developing sensing framework which has four different water quality parameter sensors such as potential hydrogen (pH), electrical conductivity (EC), temperature, and oxidation-reduction potential (ORP), (2) the second stage: developing a hardware platform that uses an Arduino for sensor array of data processing and acquisition, and finally (3) the third stage: developing soft computing framework for decision support which uses python applications and fuzzy logic. The system was tested using water from many sources such as rivers, lakes, tap water, and filtered machine. Filtered water shows the highest value of pH as the filtered machine produces alkaline water, whereas tap water shows the highest value of temperature because the water is trapped in a polyvinyl chloride (PVC) pipe. Lake water depicts the highest value of EC due to the highest amount of total suspended solids (TSS) in the water, whereas river water shows the highest value of ORP due to the highest amount of dissolved oxygen. The system can display three ranges of water quality: not acceptable (NA), adequate (ADE) and highly acceptable (HACC) ranges from 0 to 9. Filtered water is in HACC condition (ranges 7–9) because all water quality parameters are in highly acceptable ranges. Tap water shows ADE condition (ranges 4–7) because one of the water quality parameters is in adequate ranges. River and lake water depict NA conditions (ranges 0–4) as one of the water quality parameters is in not acceptable ranges. The research outcome shows that filtered water is the most reliable water source for plants due to the absence of dissolved solids and contaminants in the water. Filtered water can improve pH and reduce the risk of plant disease. This research can help farmers to monitor the quality of irrigated water which eventually prevents crop disease, enhances crop growth, and increases crop yield. Full article

Oxidation-reduction potential (ORP) sensors would constitute a robust surveillance and control solution for aeration and external carbon dosing in wastewater biological treatment processes if a clear correlation exists between the ORP values and process variables (e.g., dissolved oxygen (DO), nitrate, and chemical oxygen demand (COD). In this study, ORP values and other water quality variables were analyzed, and principal component analysis (PCA) and analysis of variance were used to study the relationships between ORP and main reactive substances under anoxic conditions. Mathematical models were then established using multiple regression analysis. The results showed that under anoxic conditions, ORP was positively correlated with nitrate, DO, and COD and negatively correlated with ammonia nitrogen, phosphate, and pH. COD had a low correlation with the ORP value change. PCA showed that the mathematical model of ORP can be established by using DO, nitrate, and phosphate, for which the adjusted R² value was 0.7195. The numeric relationships among ORP, COD, and nitrate were clearly established and applied to control external carbon dosing. A precise and clear relationship between ORP and COD offers the possibility to substitute COD monitoring for process control. Full article

The development of gustatory sensors is essential for the development of smart materials for use in robotics, and in the food, beverage, and pharmaceutical industries. We therefore designed a prototype of a rubber tongue embedded with a gustatory receptor mimicking a human tongue using our previously proposed hybrid fluid rubber (HF rubber) and an electrolytic polymerization technique. The fabricated gustatory receptor was composed of Pacinian corpuscles, which are well known and have already been elucidated as effective haptic and auditory receptors in previous studies. Moreover, the receptor has self-powered voltage generated as built-in electricity as a result of the ionized particles and molecules in the HF rubber. The utilization of a layered structure for the Pacinian corpuscles induced a typical response not only to normal and shear forces but to thermal variations. Typical gustatory characteristics, including the initial response voltage and the cyclic voltammogram form, were clearly varied by five tastes: saltiness, sourness, sweetness, bitterness, and umami. These results were due to ORP, pH, and conductivity. Full article

Shortage of water availability and awareness of the need for sustainable resource management have generated a significant increase in the use of recycled water for irrigation and processing of crops and harvest products, respectively. As a result, irrigation systems face the challenge of neutralizing plant pathogens to reduce the risk of their dispersal and the subsequent occurrence of diseases with potentially high economic impacts. We evaluated the efficacy of an innovative electrolytic disinfection system based on potassium hypochlorite (KCLO) to inactivate major pathogens in hydroponically grown tomatoes: Fusarium oxysporum (Synder and Hans), Rizocthonia solani (Kühn), Tobacco mosaic virus (TMV) and Pepino mosaic virus (PepMV). The electrolytically derived disinfectant was prepared on-site and added to the recirculating fertigation solution once a week for 60 min in an automated manner using sensor technology at a dosage of 0.5 mg of free chlorine/L (fertigation solution at pH 6.0 ± 0.3 and ORP 780 ± 31 mV). Tomato fruit yield and pathogen dispersal were determined for 16 weeks. At the applied dosage, the disinfectant has been shown to inhibit the spread of plant pathogenic fungi and, remarkably, plant viruses in recirculating fertigation solutions. Phytotoxic effects did not occur. Full article

Preventing animal-source food waste is an important pathway to reducing malnutrition and improving food system sustainability. Uncontrolled color variation due to oxidation is a source of waste as it prompts food rejection by consumers. Evaluation of oxidation–reduction potential (ORP) can help to predict and prevent oxidation and undesirable color changes. A new sensor and two modeling approaches—a phenomenological model and a reaction–diffusion model—were successfully used to predict the oxidative browning of beef ribeye steaks stored under different temperature and oxygen concentration conditions. Both models predicted similar storage durations for acceptable color, although deviating for higher and lower redness levels, which are of no interest for meat acceptance. Simulations under higher oxygen concentrations lead to a few days of delay in the redness change, as observed in practice, under modified atmosphere packaging. In meat juice, variation in ORP measured by the sensor correlated with the redness variation. However, in meat, sensors promote oxidation in the adjacent area, which is unacceptable for industrial use. This paper discusses the potential, limits, and prospects of the mathematical models and sensors, developed for beef. A strategy is proposed to couple these approaches and include the effect of microorganisms. Full article

The floating houses in Tonle Sap Lake might be one of the main factors for degradation of water quality since the people in floating houses discharge sewage and waste from their households into the lake. Therefore, the government of Cambodia has decided to move the floating houses in Chhnok Tru to the upland regions, and more than 90% of the floating houses in Chhnok Tru have already been moved in accordance with the government’s plan. However, the scientific information on water quality before and after moving the floating houses in Tonle Sap Lake is limited. Thus, this paper aimed to evaluate differences in basic water quality such as temperature, pH, dissolved oxygen (DO), oxidation–reduction potential (ORP), conductivity (Cond), and nitrate (NO₃⁻) before and after the floating houses were moved and to reveal the relationships between the floating houses and basic water quality. The water quality parameters were measured at 18 sampling sites in Chhnok Tru using an EXO sensor and NO₃⁻ was analyzed by ion chromatography (IC). Statistical analyses such as t-tests, correlation analysis, principal component analysis (PCA), and structural equation modeling (SEM) were used. The results show that the water quality was better after moving the floating houses; however, some parts of the study area were still polluted. In addition, the percentage of floating house distribution was significantly correlated with the temperature and ORP in the study area during dry and wet seasons. The obtained results are useful for making management decisions to sustainably manage the water quality in the area. Full article

Non-transform discontinuity (NTD) is one category of tectonic units along slow- and ultraslow-spreading ridges. Some NTD-related hydrothermal fields that may reflect different driving mechanisms have been documented along slow-spreading ridges, but the discrete survey strategy makes it hard to evaluate the incidence of hydrothermal activity. On ultraslow-spreading ridges, fewer NTD-related hydrothermal activities were reported. Factors contributing to the occurrence of hydrothermal activities at NTDs and whether they could be potential targets for hydrothermal exploration are poorly known. Combining turbidity and oxidation reduction potential (ORP) sensors with a near-bottom camera, Chinese Dayang cruises from 2014 to 2018 have conducted systematic towed surveys for hydrothermal activity around a large NTD along the ultraslow-spreading Southwest Indian Ridge (SWIR, 48.1–48.7° E). Five new potential hydrothermal anomaly sites (2 inferred and 3 suspected) of high or low temperature and the previously inferred Sudi hydrothermal field occurred in diverse morphotectonic settings along a 78 km long ridge axis. The calculated vent frequency (Fs, sites/100 km) was ~7.7 over the entire study area, higher than the modified value (Fs ≈ 6.5) between 48 and 52° E of SWIR. Even only for the 54 km long large NTD, three hydrothermal anomaly sites yielded an Fs of ~5.6, which is higher than that of most ridge sections and is comparable to some fast-spreading ridges with high-resolution surveys. This indicates that NTDs along ultraslow-spreading ridges could be promising areas in fertilizing hydrothermal activities. Moreover, the deeply penetrating faults on the rift valley walls and strain-focused areas may contribute to the formation of NTD-related hydrothermal circulations. We suggest that NTDs along ultraslow-spreading ridges may be potential targets for further exploration of hydrothermal activities and seafloor sulfide deposits. Full article

Submarine groundwater discharge (SGD) is an important pathway of nutrients into coastal areas. During the last decades, interest of researchers in SGDs has grown continuously. However, methods applied for SGD research usually focus on the aquifer or on the mixing processes on larger scales. The distribution of discharged water within the water column is not well investigated. Small remotely operated vehicles (ROV) equipped with environmental sensors can be used to investigate the spatial distribution of environmental parameters in the water column. Herein, a low-cost multi-sensor platform designed to investigate the spatial distribution of water quality properties is presented. The platform is based on an off-the-shelf underwater vehicle carrying various environmental sensors and a short-baseline localisation system. This contribution presents the results of SGD investigations in the area of Woodman Point (Western Australia). Various potential SGD plumes were detected using a skiff equipped with a recreational echo sounder. It was demonstrated that this inexpensive equipment could be used to detect and investigate SGDs in coastal areas. In addition, the low-cost multi-sensor platform was deployed to investigate the spatial distribution of environmental parameters including temperature (T), electric conductivity (EC), dissolved oxygen (DO), oxidation-reduction potential (ORP), pH, and dissolved organic matter fluorescence (FDOM). Three ROV surveys were conducted from different skiff locations. Analyses of the spatial distribution of the environmental parameters allowed the identification of nine potential SGD plumes. At the same locations, plumes were identified during the sonar surveys. In addition, fuzzy logic was used for the fusion of salinity, DO, and FDOM readings in order to enhance SGD detection capability of the designed multi-sensor system. The fuzzy logic approach identified 293 data points as potential within a SGD plume. Average minimum-distance between these points and the identified SGD plumes was 0.5 m and 0.42 m smaller than the minimum-distance average of the remaining data points of survey one and three respectively. It was shown that low-cost ROVs, equipped with environmental sensors, could be an important tool for the investigation of the spatio-temporal behaviour of SGD sites. This method allows continuous mapping of environmental parameters with a high spatial and temporal resolution. However, to obtain deeper insights into the influence of SGDs on the nearshore areas, this method should be combined with other well-established methods for SGD investigation, such as pore water sampling, remote sensing, or groundwater monitoring. Full article