Journal articles: 'Biological Early Warning System'

1

Kim, Sung-Yong, Ki-Yong Kwon, and Won-Don Lee. "Biological Early Warning System for Toxicity Detection." Journal of the Korean Institute of Information and Communication Engineering 14, no. 9 (September 30, 2010): 1979–86. http://dx.doi.org/10.6109/jkiice.2010.14.9.1979.

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Yang, Haiqing. "Biological Early Warning System for Prawn Aquiculture." Procedia Environmental Sciences 10 (2011): 660–65. http://dx.doi.org/10.1016/j.proenv.2011.09.106.

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Balk, F., P. C. Okkerman, C. A. M. van Helmond, F. Noppert, and I. van der Putte. "Biological Early Warning Systems for Surface Water and Industrial Effluents." Water Science and Technology 29, no. 3 (February 1, 1994): 211–13. http://dx.doi.org/10.2166/wst.1994.0104.

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Within the framework of the International Rhine Action Programme and the EC ACE-Programme in the field of the environment (regulation EC.224/87) the sensitivity and reliability of biological early warning systems are being tested. The effectiveness of these systems for continuous water quality monitoring is being assessed, using surface water and industrial effluents. The systems tested are a fish and a waterflea early warning system. From the results it is concluded that both types of biological early warning systems in combination with physico-chemical monitoring increase the effectiveness of monitoring pollution levels in surface water. Fish early warning systems can be important tools in reducing water pollution by industries.

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de Zwart, Dick, Kees J. M. Kramer, and Henk A. Jenner. "Practical experiences with the biological early warning system “mosselmonitor”." Environmental Toxicology & Water Quality 10, no. 4 (November 1995): 237–47. http://dx.doi.org/10.1002/tox.2530100403.

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Lee, Jong-Chan, and Won-Don Lee. "Biological Early Warning Systems using UChoo Algorithm." Journal of the Korean Institute of Information and Communication Engineering 16, no. 1 (January 31, 2012): 33–40. http://dx.doi.org/10.6109/jkiice.2012.16.1.033.

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Sluyts, Hilde, François Van Hoof, Anja Cornet, and Jozef Paulussen. "A dynamic new alarm system for use in biological early warning systems." Environmental Toxicology and Chemistry 15, no. 8 (August 1996): 1317–23. http://dx.doi.org/10.1002/etc.5620150809.

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Leynen, M., T. Van den Berckt, J. M. Aerts, B. Castelein, D. Berckmans, and F. Ollevier. "The use of Tubificidae in a biological early warning system." Environmental Pollution 105, no. 1 (April 1999): 151–54. http://dx.doi.org/10.1016/s0269-7491(98)00144-4.

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Grekov, Aleksandr N., Aleksey A. Kabanov, Elena V. Vyshkvarkova, and Valeriy V. Trusevich. "Anomaly Detection in Biological Early Warning Systems Using Unsupervised Machine Learning." Sensors 23, no. 5 (March 1, 2023): 2687. http://dx.doi.org/10.3390/s23052687.

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The use of bivalve mollusks as bioindicators in automated monitoring systems can provide real-time detection of emergency situations associated with the pollution of aquatic environments. The behavioral reactions of Unio pictorum (Linnaeus, 1758) were employed in the development of a comprehensive automated monitoring system for aquatic environments by the authors. The study used experimental data obtained by an automated system from the Chernaya River in the Sevastopol region of the Crimean Peninsula. Four traditional unsupervised machine learning techniques were implemented to detect emergency signals in the activity of bivalves: elliptic envelope, isolation forest (iForest), one-class support vector machine (SVM), and local outlier factor (LOF). The results showed that the use of the elliptic envelope, iForest, and LOF methods with proper hyperparameter tuning can detect anomalies in mollusk activity data without false alarms, with an F1 score of 1. A comparison of anomaly detection times revealed that the iForest method is the most efficient. These findings demonstrate the potential of using bivalve mollusks as bioindicators in automated monitoring systems for the early detection of pollution in aquatic environments.

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Amorim, João, Miguel Fernandes, Vitor Vasconcelos, and Luis Oliva Teles. "Stress test of a biological early warning system with zebrafish (Danio rerio)." Ecotoxicology 26, no. 1 (October 7, 2016): 13–21. http://dx.doi.org/10.1007/s10646-016-1736-5.

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Chen, Qiuwen, Jinfeng Ma, Zijian Wang, and Guoxian Huang. "Biological early warning and emergency management support system for water pollution accident." Transactions of Tianjin University 18, no. 3 (June 2012): 201–5. http://dx.doi.org/10.1007/s12209-012-1662-4.

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Bott, Charles, INES D. S. HENRIQUES, RICHARD T. KELLY, JENNIFER L. DAUPHINAIS, and NANCY G. LOVE. "WERF: Upset Early Warning Systems For Biological Wastewater Treatment." Proceedings of the Water Environment Federation 2002, no. 7 (January 1, 2002): 786–816. http://dx.doi.org/10.2175/193864702785073163.

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Foran, J. A., and T. M. Brosnan. "Early warning systems for hazardous biological agents in potable water." Environmental Health Perspectives 108, no. 10 (October 2000): 993–95. http://dx.doi.org/10.1289/ehp.00108993.

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Di Giacinto, Federica, Miriam Berti, Luigi Carbone, Riccardo Caprioli, Valentina Colaiuda, Annalina Lombardi, Barbara Tomassetti, et al. "Biological Early Warning Systems: The Experience in the Gran Sasso-Sirente Aquifer." Water 13, no. 11 (May 29, 2021): 1529. http://dx.doi.org/10.3390/w13111529.

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Biological early warning systems (BEWS) are installed worldwide for the continuous control of water intended for multiple uses. Sentinel aquatic organisms can alert us to contaminant presence through their physiological or behavioural alterations. The present study is aimed at sharing the experience acquired with water biomonitoring of the Gran Sasso-Sirente (GS-S) aquifer. It represents the major source of the Abruzzi region surface water, also intended as drinkable and for irrigation use. Besides the biomonitoring of drinkable water of the Teramo Province made by Daphnia Toximeter and irrigation water of the L’Aquila Province by Algae Toximeter, a novel sensor named “SmartShell” has been developed to register the behaviour of the “pea clam” P. casertanum, an autochthonous small bivalve living in the Nature 2000 site “Tirino River spring”. The valve movements have been recorded directly on the field. Its behavioural rhythms have been analysed through spectral analyses, providing the basis for further investigations on their alterations as early warnings and allowing us to propose this autochthonous bivalve species as a novel sentinel organism for spring water.

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Harris, Mallory J., Simon I. Hay, and John M. Drake. "Early warning signals of malaria resurgence in Kericho, Kenya." Biology Letters 16, no. 3 (March 2020): 20190713. http://dx.doi.org/10.1098/rsbl.2019.0713.

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Campaigns to eliminate infectious diseases could be greatly aided by methods for providing early warning signals of resurgence. Theory predicts that as a disease transmission system undergoes a transition from stability at the disease-free equilibrium to sustained transmission, it will exhibit characteristic behaviours known as critical slowing down, referring to the speed at which fluctuations in the number of cases are dampened, for instance the extinction of a local transmission chain after infection from an imported case. These phenomena include increases in several summary statistics, including lag-1 autocorrelation, variance and the first difference of variance. Here, we report the first empirical test of this prediction during the resurgence of malaria in Kericho, Kenya. For 10 summary statistics, we measured the approach to criticality in a rolling window to quantify the size of effect and directions. Nine of the statistics increased as predicted and variance, the first difference of variance, autocovariance, lag-1 autocorrelation and decay time returned early warning signals of critical slowing down based on permutation tests. These results show that time series of disease incidence collected through ordinary surveillance activities may exhibit characteristic signatures prior to an outbreak, a phenomenon that may be quite general among infectious disease systems.

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15

Zhou, Lihong. "The Monitoring and Early Warning System of Water Biological Environment Based on Machine Vision." Mathematical Problems in Engineering 2022 (June 24, 2022): 1–7. http://dx.doi.org/10.1155/2022/8280706.

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Water contaminated by microorganisms can lead to the outbreak and prevalence of various diseases, which seriously threaten the health of people. In the monitoring of the water biological environment, the traditional methods have low detection sensitivity and low efficiency, so it is urgent to design a water biological monitoring system with low cost and high monitoring efficiency. Machine vision has the advantages of fast speed, appropriate precision, and strong anti-interference ability, which has been greatly developed in recent years. In this paper, the monitoring and early warning system of the water biological environment is built, in which the SVM algorithm is applied to image processing and feature extraction, and each module of the system is designed. Finally, the computational complexity of the system algorithm and the detection accuracy of the system are tested, and the results show that the system has the advantages of low cost, low computational complexity, and high monitoring efficiency, which can provide a reference for water resources protection.

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Zhang, Jianfei, Zhongpeng Wu, and Chong An. "Research on the detection and early warning technology of harmful marine organisms in the water intake of nuclear power plant by 3D image sonar." E3S Web of Conferences 290 (2021): 03013. http://dx.doi.org/10.1051/e3sconf/202129003013.

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In view of the frequent water intake blockage caused by marine biological invasion in many nuclear power plants, which affects the safety of cold source in nuclear power plants, a defense system in depth including marine biological identification, detection, early warning and hierarchical response is established through investigation and analysis of the causes of the event. Underwater acoustic high-resolution multi beam detection method is used to detect jellyfish, hairy shrimp and other marine organisms, The echo characteristics are obtained, the distribution density in sensitive sea area is analyzed, and the effective early warning judgment is given. Among them, detection and early warning is the front-end disposal measure, which can provide accurate and timely marine biological information for the subsequent hierarchical response. At the same time, it can replace the underwater inspection work of divers, reduce the risk of divers, reduce the risk of industrial safety, and improve the reliability of cold source.

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17

Jarder, Samantha Louise N., Raniel Cris L. Macabare, Salvador G. Oleivar, Abraham Matthew S. Carandang, Patrick Shaun N. Ngo, Richard M. De Jesus, Lessandro Estelito O. Garciano, and Andres Winston C. Oreta. "Multi-Hazard Early Warning System (MHEWS) Assessment Methodology for Schools." International Journal on Advanced Science, Engineering and Information Technology 11, no. 3 (June 10, 2021): 937. http://dx.doi.org/10.18517/ijaseit.11.3.14535.

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Duchev, Z., O. Distl, and E. Groeneveld. "Early warning system for loss of diversity in European livestock breeds." Archives Animal Breeding 49, no. 6 (October 10, 2006): 521–31. http://dx.doi.org/10.5194/aab-49-521-2006.

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Abstract. Towards the end of the previous century the increasing erosion of biological diversity in livestock was recognized by the animal breeders as an area which needs monitoring and conservation measures. For that purpose various national, regional and global infrastructures was put in place by governmental and non-governmental organizations like European Association for Animal Production (EAAP), Food and Agriculture Organization (FAO) of the United Nations and Rare Breeds International, etc. These organizations have developed a number of methods for estimation the risk status of the breed. However, the different systems use different parameters and thresholds and are hard to compare. Several attempts for uniform European criterion have been made, but still no consensus has been reached. In this study we continue the work of the Animal Genetic Resources group of EAAP towards the uniform criterion based on the effective population size, the expected number of breeding females and the global population. Our main contribution is the novel approach in handling the parameter global population, allowing its external parameterization. The criterion was applied to 21 pig breeds from 8 European countries and the results show clear not at risk status of the big international breeds.

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19

Temmink, H., P. Vanrolleghem, A. Klapwijk, and W. Verstraete. "Biological Early Warning Systems for Toxicity Based on Activated Sludge Respirometry." Water Science and Technology 28, no. 11-12 (December 1, 1993): 415–25. http://dx.doi.org/10.2166/wst.1993.0681.

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The proper operation of the activated sludge process is endangered by toxic spills in the wastewater that has to be treated. Therefore there is a need for so called biological early warning systems (BEWSs) that can detect toxicity for the activated sludge process and allow operators to take protective actions. Two independently developed BEWSs are described and evaluated. Both systems are based on the on-line measurement of the respiration rate of activated sludge taken from the plant to be protected. Their practical implementation however is different with respect to the way the suspicious wastewater is brought into contact with the sludge. It is illustrated what the consequences of the design choices are with respect to the sensitivity, the response time and the positioning at the treatment plant of these BEWSs.

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Heine, W., I. Sekoulov, H. Burkhardt, L. Bergen, and J. Behrendt. "Early warning-system for operation-failures in biological stages of WWTPs by on-line image analysis." Water Science and Technology 46, no. 4-5 (August 1, 2002): 117–24. http://dx.doi.org/10.2166/wst.2002.0566.

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By the observation and evaluation of the microscopic picture of activated sludge samples it is possible to introduce another biological parameter additional to conventional physico-chemical parameters for the control of biological stages of waste water treatment plants. Considering the fact that parameters like floc size and floc size distribution, structure of the flocs (compact/open), shape of the flocs (round/irregular) allow perceptions of the adjusted operation conditions of the biological stages, evidence for changing operation conditions or threatening operation disturbances can be recognised. This recognition takes place at a very early phase, because the morphology of activated sludge flocs reacts very fast to changing conditions. An automatic image analysis of activated sludge floc pictures would enable the introduction of a new sum parameter to enhance operation control of aeration tanks. By a statistical evaluation of the processed sludge images several parameters can be used to describe the alteration of activated sludge flocs characteristics. With these biological parameters it is possible to detect altered operation conditions or threatening or existing operation problems at an early phase. Thus it is possible to plan suitable countermeasures. Furthermore, the microscopic picture is the only parameter, that gives important information about the structure of the activated sludge flocs and the biozenosis. In comparison with the mainly used physico-chemical parameters, that just give information about the inlet and outlet of the wastewater treatment plants, the microscopic picture is the only parameter that gives information about the biology of the wastewater treatment process. By means of this biological parameter an improved control and regulation of the biological stages of wastewater treatment plants can be obtained.

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21

Nunes, António Júlio, Paulo Paixão, Jorge Proença, and RicardoJ N. Bettencourt da Silva. "Early Warning of Suspected Doping from Biological Passport Based on Multivariate Trends." International Journal of Sports Medicine 41, no. 01 (November 20, 2019): 44–53. http://dx.doi.org/10.1055/a-1019-7774.

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AbstractThe indirect identification of doping in sports can be performed by assessing athletesʼ hematological perturbations from the analysis of blood collected on different occasions. Because prosecution for doping based on this information requires expensive and time-consuming interpretation of blood analysis results by various expert hematologists, mathematical data screening is performed to decide which cases should be forwarded to hematologists. The current Bayesian and univariate screening of data does not process the multivariate trends of blood parameters or take the time interval between samplings into account. This work presents a computational tool that overcomes these limitations by calculating a single score, the hematological perturbation index (HPIx), for which a threshold is defined above which hematologists should be asked to assess the athleteʼs biological passport. The doping detection from this index, normalized for days difference between samplings based on 3, 4 or 5 consecutive samplings, is associated with true positive result rates (TP) not below 98% and false positive result rates (FP) less than 0.9%. Therefore, this tool can be useful as an early warning system of hematological perturbations to decide which athletes should be more closely monitored and which biological passports should be forwarded to hematologists for medical interpretation of data.

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Chmist, Joanna, Krzysztof Szoszkiewicz, and Mateusz Hämmerling. "SELECTION OF THE MOST EFFECTIVE BIOLOGICAL EARLY WARNING SYSTEM, BASED ON AHP AND REMBRANDT ANALYSIS." Acta Scientiarum Polonorum Formatio Circumiectus 1 (2019): 95–102. http://dx.doi.org/10.15576/asp.fc/2018.17.1.95.

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23

Bae, Mi-Jung, and Young-Seuk Park. "Biological early warning system based on the responses of aquatic organisms to disturbances: A review." Science of The Total Environment 466-467 (January 2014): 635–49. http://dx.doi.org/10.1016/j.scitotenv.2013.07.075.

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Sri Lestari, Veronika Nugraheni, Dwi Cahyono, and Sri Susilowati. "Designing Early Warning System for The Impact of Industrial Development Waste by Using pH Control System." International Journal of Engineering & Technology 7, no. 2.14 (April 15, 2018): 555. http://dx.doi.org/10.14419/ijet.v7i2.11581.

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Environment is inseparable from human life. Human negligence in building industry without caring the impact on environment can damage the physical and biological environment slowly and indirectly. Therefore an effort to preserve the quality of environment, especially for the environment adjacent to the settlement, is necessary and can be performed in various ways including technology utilization. Technology develops rapidly and electronic devices have become one compulsory device to be owned. Wastewater is industrial waste should be controlled prior to passing surrounding environment to avoid pollution. One way to control it is controlling its pH of, this is performed by early warning on pH level. This paper focused on designing control device for industrial waste water pH that is able to inform an early when on concentration of industrial waste water under normal limit water.

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Love, N. "Upset Early Warning Systems for Biological Treatment Processes: Source and effect relationships." Water Intelligence Online 4 (December 30, 2015): 9781780404455. http://dx.doi.org/10.2166/9781780404455.

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Wang, Gang, Yuanyuan Li, and Xiufen Zou. "Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis." Computational and Mathematical Methods in Medicine 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7560758.

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Many complex diseases (chronic disease onset, development and differentiation, self-assembly, etc.) are reminiscent of phase transitions in a dynamical system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. Understanding such nonlinear behaviors is critical to dissect the multiple genetic/environmental factors that together shape the genetic and physiological landscape underlying basic biological functions and to identify the key driving molecules. Based on stochastic differential equation (SDE) model, we theoretically derive three statistical indicators, that is, coefficient of variation (CV), transformed Pearson’s correlation coefficient (TPC), and transformed probability distribution (TPD), to identify critical transitions and detect the early-warning signals of the phase transition in complex diseases. To verify the effectiveness of these early-warning indexes, we use high-throughput data for three complex diseases, including influenza caused by either H3N2 or H1N1 and acute lung injury, to extract the dynamical network biomarkers (DNBs) responsible for catastrophic transition into the disease state from predisease state. The numerical results indicate that the derived indicators provide a data-based quantitative analysis for early-warning signals for critical transitions in complex diseases or other dynamical systems.

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Riyansyah, Muhammad, Pratama Budi Wijayanto, Bambang Riyanto Trilaksono, Seno Adi Putra, and Dina Shona Laila. "Real Time Bridge Dynamic Response: Bridge Condition Assessment and Early Warning System." International Journal on Advanced Science, Engineering and Information Technology 10, no. 1 (February 28, 2020): 325. http://dx.doi.org/10.18517/ijaseit.10.1.9463.

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Smith, G. E., D. L. Cooper, P. Loveridge, F. Chinemana, E. Gerard, and N. Verlander. "A national syndromic surveillance system for England and Wales using calls to a telephone helpline." Eurosurveillance 11, no. 12 (December 1, 2006): 9–10. http://dx.doi.org/10.2807/esm.11.12.00667-en.

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Routine primary care data provide the means to monitor a variety of syndromes which could give early warning of health protection issues. In the United Kingdom, a national syndromic surveillance system, operated jointly by the UK Health Protection Agency (HPA) and NHS Direct (a national telephone health helpline), examines symptoms reported to NHS Direct. The aim of the system is to identify an increase in syndromes indicative of common infections and diseases, or the early stages of illness caused by the deliberate release of a biological or chemical agent. Data relating to 11 key symptoms/syndromes are received electronically from all 22 NHS Direct call centres covering England and Wales and analysed by the HPA on a daily basis. Statistically significant excesses in calls are automatically highlighted and assessed by a multi-disciplinary team. Although the surveillance system has characterised many sudden rises in syndromes reported to NHS Direct, no evidence of a biological or chemical attack has been detected. Benefits of this work, however, are early warning and tracking of rises in community morbidity (e.g. influenza-like illness, heatstroke); providing reassurance during times of perceived high risk (e.g. after the 7 July 2005 London bombs and December 2005 Buncefield oil depot fire); and timely surveillance data for influenza pandemic planning and epidemic modeling.

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Jeong, T. Y., J. Jeon, and S. D. Kim. "Development and evaluation of new behavioral indexes for a biological early warning system using Daphnia magna." Drinking Water Engineering and Science 7, no. 1 (January 14, 2014): 1–9. http://dx.doi.org/10.5194/dwes-7-1-2014.

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Abstract. New behavioral indexes including combined index (CI), distribution index (DI), toxic index (TI), and altitude index (AI) for a biological early warning system (BEWS) were developed and evaluated using Daphnia magna in this study. The sensitivity and stability of each index were compared to evaluate the performance of the indexes through a real-time exposure test with a synthetic copper solution. The applicability of the CI to the field sample was evaluated through an effluent exposure test. The proportional relationship between toxicity level and magnitude of response was much lower in the effluent due to the complexity of water than in the copper solution. The results showed that the CI was most sensitive among the three indexes, while the DI was confirmed as the most useful index among the individual indexes. The combined index (CI) shows not only sensitivity but also stability in normal conditions below the statistically significant threshold (p < 0.01), whereas the individual indexes displayed unstable index values in normal conditions (p > 0.01). The CI improved performance of the BEWS in terms of sensitivity and stability, and it was confirmed as the higher correlation coefficient between the magnitude of the index and the toxicity level of the water sample.

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Jeong, T. Y., J. H. Jeon, and S. D. Kim. "Development and evaluation of new behavioral indexes for a biological early warning system using Daphnia magna." Drinking Water Engineering and Science Discussions 6, no. 1 (March 5, 2013): 39–58. http://dx.doi.org/10.5194/dwesd-6-39-2013.

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Abstract. New behavioral indexes including combined index (CI), distribution index (DI), toxic index (TI), and altitude index (AI) for a biological early warning system (BEWS) were developed and evaluated using Daphnia magna in this study. The sensitivity and stability of each index were compared to evaluate the performance of the indexes through a real-time exposure test with a synthetic copper solution. The applicability of the CI to the field sample was evaluated through an effluent exposure test. The proportional relationship between toxicity level and magnitude of response was much lower in the effluent due to the complexity of water than in the copper solution. The results showed that the CI was most sensitive among the three indexes, while the DI was confirmed as the most useful index among the individual indexes. The combined index (CI) shows not only sensitivity but also stability in normal conditions below the statistically significant threshold (p < 0.01), whereas the individual indexes displayed unstable index values in normal conditions (p > 0.01). The CI improved performance of the BEWS in terms of sensitivity and stability, and it was confirmed as the higher correlation coefficient between the magnitude of the index and the toxicity level of the water sample.

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Giari, Luisa, Fabio Vincenzi, Elisa Anna Fano, Ivano Graldi, Fernando Gelli, and Giuseppe Castaldelli. "Sensitivity to selected contaminants in a biological early warning system using Anodonta woodiana (Mollusca)." Water SA 43, no. 2 (April 21, 2017): 200. http://dx.doi.org/10.4314/wsa.v43i2.04.

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Jeong, Tae-Yong, and Myrna J. Simpson. "Daphnia magna metabolic profiling as a promising water quality parameter for the biological early warning system." Water Research 166 (December 2019): 115033. http://dx.doi.org/10.1016/j.watres.2019.115033.

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Hong, Seil, Il Choi, Byung Lim, and Hyunook Kim. "A DO- and pH-Based Early Warning System of Nitrification Inhibition for Biological Nitrogen Removal Processes." Sensors 12, no. 12 (November 26, 2012): 16334–52. http://dx.doi.org/10.3390/s121216334.

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Stone, Wendy, Tobi M. Louw, Marthinus J. Booysen, and Gideon M. Wolfaardt. "Canary in the coliform mine: Exploring the industrial application limits of a microbial respiration alarm system." PLOS ONE 16, no. 3 (March 4, 2021): e0247910. http://dx.doi.org/10.1371/journal.pone.0247910.

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Fundamental ecological principles of ecosystem-level respiration are extensively applied in greenhouse gas and elemental cycle studies. A laboratory system termed CEMS (Carbon Dioxide Evolution Measurement System), developed to explore microbial biofilm growth and metabolic responses, was evaluated as an early-warning system for microbial disturbances in industrial settings: in (a) potable water system contamination, and (b) bioreactor inhibition. Respiration was detected as CO2 production, rather than O2 consumption, including aerobic and anaerobic metabolism. Design, thresholds, and benefits of the remote CO2 monitoring technology were described. Headspace CO2 correlated with contamination levels, as well as chemical (R2 > 0.83–0.96) and microbiological water quality indicators (R2 > 0.78–0.88). Detection thresholds were limiting factors in monitoring drinking water to national and international standards (0 CFU/100 mL fecal coliforms) in both open- (>1500 CFU/mL) and closed-loop CO2 measuring regimes (>100 CFU/100 mL). However, closed-loop detection thresholds allow for the detection of significant contamination events, and monitoring less stringent systems such as irrigation water (<100 CFU/mL). Whole-system respiration was effectively harnessed as an early-warning system in bioreactor performance monitoring. Models were used to deconvolute biological CO2 fluctuations from chemical CO2 dynamics, to optimize this real-time, sustainable, low-waste technology, facilitating timeous responses to biological disturbances in bioreactors.

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Tang, Qinhua, Xingxing Cen, and Changqing Pan. "Explainable and efficient deep early warning system for cardiac arrest prediction from electronic health records." Mathematical Biosciences and Engineering 19, no. 10 (2022): 9825–41. http://dx.doi.org/10.3934/mbe.2022457.

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<abstract> <p>Cardiac arrest (CA) is a fatal acute event. The development of new CA early warning system based on time series of vital signs from electronic health records (EHR) has great potential to reduce CA damage. In this process, recursive architecture-based deep learning, as a powerful tool for time series data processing, enables automatically extract features from various monitoring clinical parameters and to further improve the performance for acute critical illness prediction. However, the unexplainable nature and excessive time caused by black box structure with poor parallelism are the limitations of its development, especially in the CA clinical application with strict requirement of emergency treatment and low hidden dangers. In this study, we present an explainable and efficient deep early warning system for CA prediction, which features are captured by an efficient temporal convolutional network (TCN) on EHR clinical parameters sequence and explained by deep Taylor decomposition (DTD) theoretical framework. To demonstrate the feasibility of our method and further evaluate its performance, prediction and explanation experiments were performed. Experimental results show that our method achieves superior CA prediction accuracy compared with standard national early warning score (NEWS), in terms of overall AUROC (0.850 Vs. 0.476) and F1-Score (0.750 Vs. 0.450). Furthermore, our method improves the interpretability and efficiency of deep learning-based CA early warning system. It provides the relevance of prediction results for each clinical parameter and about 1.7 times speed enhancement for system calculation compared with the long short-term memory network.</p> </abstract>

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van der Schalie, William H., Tommy R. Shedd, Paul L. Knechtges, and Mark W. Widder. "Using higher organisms in biological early warning systems for real-time toxicity detection." Biosensors and Bioelectronics 16, no. 7-8 (September 2001): 457–65. http://dx.doi.org/10.1016/s0956-5663(01)00160-9.

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Brown, Molly E., Stephen Mugo, Sebastian Petersen, and Dominik Klauser. "Designing a Pest and Disease Outbreak Warning System for Farmers, Agronomists and Agricultural Input Distributors in East Africa." Insects 13, no. 3 (February 26, 2022): 232. http://dx.doi.org/10.3390/insects13030232.

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Early warnings of the risks of pest and disease outbreaks are becoming more urgent, with substantial increases in threats to agriculture from invasive pests. With geospatial data improvements in quality and timeliness, models and analytical systems can be used to estimate potential areas at high risk of yield impacts. The development of decision support systems requires an understanding of what information is needed, when it is needed, and at what resolution and accuracy. Here, we report on a professional review conducted with 53 professional agronomists, retailers, distributors, and growers in East Africa working with the Syngenta Foundation for Sustainable Agriculture. The results showed that respondents reported fall armyworm, stemborers and aphids as being among the most common pests, and that crop diversification was a key strategy to reduce their impact. Chemical and cultural controls were the most common strategies for fall armyworm (FAW) control, and biological control was the least known and least used method. Of the cultural control methods, monitoring and scouting, early planting, and crop rotation with non-host crops were most used. Although pests reduced production, only 55% of respondents were familiar with early warning tools, showing the need for predictive systems that can improve farmer response.

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Fernandes, Miguel, João Amorim, Vitor Vasconcelos, and Luis Oliva Teles. "Resilience assessment of a biological early warning system based on the locomotor behavior of zebrafish (Danio rerio)." Environmental Science and Pollution Research 23, no. 18 (June 20, 2016): 18858–68. http://dx.doi.org/10.1007/s11356-016-7085-3.

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Boettiger, Carl, and Alan Hastings. "Early warning signals and the prosecutor's fallacy." Proceedings of the Royal Society B: Biological Sciences 279, no. 1748 (October 10, 2012): 4734–39. http://dx.doi.org/10.1098/rspb.2012.2085.

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Early warning signals have been proposed to forecast the possibility of a critical transition, such as the eutrophication of a lake, the collapse of a coral reef or the end of a glacial period. Because such transitions often unfold on temporal and spatial scales that can be difficult to approach by experimental manipulation, research has often relied on historical observations as a source of natural experiments. Here, we examine a critical difference between selecting systems for study based on the fact that we have observed a critical transition and those systems for which we wish to forecast the approach of a transition. This difference arises by conditionally selecting systems known to experience a transition of some sort and failing to account for the bias this introduces—a statistical error often known as the prosecutor's fallacy. By analysing simulated systems that have experienced transitions purely by chance, we reveal an elevated rate of false-positives in common warning signal statistics. We further demonstrate a model-based approach that is less subject to this bias than those more commonly used summary statistics. We note that experimental studies with replicates avoid this pitfall entirely.

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Umar, Aminu, Charles A. Ameh, Francis Muriithi, and Matthews Mathai. "Early warning systems in obstetrics: A systematic literature review." PLOS ONE 14, no. 5 (May 31, 2019): e0217864. http://dx.doi.org/10.1371/journal.pone.0217864.

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Schirdewahn, Frederik, Hartmut H. K. Lentz, Vittoria Colizza, Andreas Koher, Philipp Hövel, and Beatriz Vidondo. "Early warning of infectious disease outbreaks on cattle-transport networks." PLOS ONE 16, no. 1 (January 6, 2021): e0244999. http://dx.doi.org/10.1371/journal.pone.0244999.

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Surveillance of infectious diseases in livestock is traditionally carried out at the farms, which are the typical units of epidemiological investigations and interventions. In Central and Western Europe, high-quality, long-term time series of animal transports have become available and this opens the possibility to new approaches like sentinel surveillance. By comparing a sentinel surveillance scheme based on markets to one based on farms, the primary aim of this paper is to identify the smallest set of sentinel holdings that would reliably and timely detect emergent disease outbreaks in Swiss cattle. Using a data-driven approach, we simulate the spread of infectious diseases according to the reported or available daily cattle transport data in Switzerland over a four year period. Investigating the efficiency of surveillance at either market or farm level, we find that the most efficient early warning surveillance system [the smallest set of sentinels that timely and reliably detect outbreaks (small outbreaks at detection, short detection delays)] would be based on the former, rather than the latter. We show that a detection probability of 86% can be achieved by monitoring all 137 markets in the network. Additional 250 farm sentinels—selected according to their risk—need to be placed under surveillance so that the probability of first hitting one of these farm sentinels is at least as high as the probability of first hitting a market. Combining all markets and 1000 farms with highest risk of infection, these two levels together will lead to a detection probability of 99%. We conclude that the design of animal surveillance systems greatly benefits from the use of the existing abundant and detailed animal transport data especially in the case of highly dynamic cattle transport networks. Sentinel surveillance approaches can be tailored to complement existing farm risk-based and syndromic surveillance approaches.

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Wlodkowic, Donald, and Tomasz M. Karpiński. "Live-Cell Systems in Real-Time Biomonitoring of Water Pollution: Practical Considerations and Future Perspectives." Sensors 21, no. 21 (October 23, 2021): 7028. http://dx.doi.org/10.3390/s21217028.

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Continuous monitoring and early warning of potential water contamination with toxic chemicals is of paramount importance for human health and sustainable food production. During the last few decades there have been noteworthy advances in technologies for the automated sensing of physicochemical parameters of water. These do not translate well into online monitoring of chemical pollutants since most of them are either incapable of real-time detection or unable to detect impacts on biological organisms. As a result, biological early warning systems have been proposed to supplement conventional water quality test strategies. Such systems can continuously evaluate physiological parameters of suitable aquatic species and alert the user to the presence of toxicants. In this regard, single cellular organisms, such as bacteria, cyanobacteria, micro-algae and vertebrate cell lines, offer promising avenues for development of water biosensors. Historically, only a handful of systems utilising single-cell organisms have been deployed as established online water biomonitoring tools. Recent advances in recombinant microorganisms, cell immobilisation techniques, live-cell microarrays and microfluidic Lab-on-a-Chip technologies open new avenues to develop miniaturised systems capable of detecting a broad range of water contaminants. In experimental settings, they have been shown as sensitive and rapid biosensors with capabilities to detect traces of contaminants. In this work, we critically review the recent advances and practical prospects of biological early warning systems based on live-cell biosensors. We demonstrate historical deployment successes, technological innovations, as well as current challenges for the broader deployment of live-cell biosensors in the monitoring of water quality.

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Foo, Jerome Clifford, Hamid Reza Noori, Ikuhiro Yamaguchi, Valentina Vengeliene, Alejandro Cosa-Linan, Toru Nakamura, Kenji Morita, Rainer Spanagel, and Yoshiharu Yamamoto. "Dynamical state transitions into addictive behaviour and their early-warning signals." Proceedings of the Royal Society B: Biological Sciences 284, no. 1860 (August 2, 2017): 20170882. http://dx.doi.org/10.1098/rspb.2017.0882.

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The theory of critical transitions in complex systems (ecosystems, climate, etc.), and especially its ability to predict abrupt changes by early-warning signals based on analysis of fluctuations close to tipping points, is seen as a promising avenue to study disease dynamics. However, the biomedical field still lacks a clear demonstration of this concept. Here, we used a well-established animal model in which initial alcohol exposure followed by deprivation and subsequent reintroduction of alcohol induces excessive alcohol drinking as an example of disease onset. Intensive longitudinal data (ILD) of rat drinking behaviour and locomotor activity were acquired by a fully automated drinkometer device over 14 weeks. Dynamical characteristics of ILD were extracted using a multi-scale computational approach. Our analysis shows a transition into addictive behaviour preceded by early-warning signals such as instability of drinking patterns and locomotor circadian rhythms, and a resultant increase in low frequency, ultradian rhythms during the first week of deprivation. We find evidence that during prolonged deprivation, a critical transition takes place pushing the system to excessive alcohol consumption. This study provides an adaptable framework for processing ILD from clinical studies and for examining disease dynamics and early-warning signals in the biomedical field.

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Cera, Alessandra, Simona Ceschin, Floriano Del Grosso, Lorenzo Traversetti, and Massimiliano Scalici. "Correlating ecotoxicological early-warning systems to biotic indices to assess riverine teratogenic contamination." Marine and Freshwater Research 71, no. 8 (2020): 1033. http://dx.doi.org/10.1071/mf18471.

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We constructed a new ecotoxicological tool to test for the presence of teratogens in rivers by exploiting the regenerative capabilities of Hydra vulgaris because using living organisms is considered good practice in environmental monitoring for detecting detrimental pressures. Outputs on the Hydra assay were integrated with two biotic indices based on benthic invertebrates and macrophytes to evaluate whether the assay acts as a tool for detecting generalised freshwater conditions or as a biological test model revealing only the effects of dissolved teratogens. Several hypostomae of H. vulgaris were reared in waters collected in diverse southern central Latium rivers, where physiochemical descriptors were surveyed for environmental characterisation. The regeneration rate and amount of aberrations were evaluated to obtain a teratogenic risk index (TRI) score and then compared with the control. TRI calculations showed 4 sites (18.18%) in Class I (no risk), 15 sites (68.18%) in Class II (low risk), 2 sites (9.09%) in Class III (moderate risk) and 1 site (4.55%) in Class IV (high risk). No Class V sites (very high risk) were found. No significant correlations emerged among physicochemical parameters (except for PO43–), environmental descriptors, Simpson diversity indices and biotic indices and the TRI. These results promote an integrated approach to improving links between biological and ecological responses to anthropogenic impacts.

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Lenton, Timothy M. "Tipping positive change." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1794 (January 27, 2020): 20190123. http://dx.doi.org/10.1098/rstb.2019.0123.

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Tipping points exist in social, ecological and climate systems and those systems are increasingly causally intertwined in the Anthropocene. Climate change and biosphere degradation have advanced to the point where we are already triggering damaging environmental tipping points, and to avoid worse ones ahead will require finding and triggering positive tipping points towards sustainability in coupled social, ecological and technological systems. To help with that I outline how tipping points can occur in continuous dynamical systems and in networks, the causal interactions that can occur between tipping events across different types and scales of system—including the conditions required to trigger tipping cascades, the potential for early warning signals of tipping points, and how they could inform deliberate tipping of positive change. In particular, the same methods that can provide early warning of damaging environmental tipping points can be used to detect when a socio-technical or socio-ecological system is most sensitive to being deliberately tipped in a desirable direction. I provide some example targets for such deliberate tipping of positive change. This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions'.

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Novianty, Astri, Carmadi Machbub, Sri Widiyantoro, Irwan Meilano, and Daryono. "Tsunami Potential Prediction using Seismic Features and Artificial Neural Network for Tsunami Early Warning System." International Journal on Advanced Science, Engineering and Information Technology 12, no. 1 (January 21, 2022): 16. http://dx.doi.org/10.18517/ijaseit.12.1.14237.

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Manik, Lindung Parningotan, Hatim Albasri, Reny Puspasari, Aris Yaman, Shidiq Al Hakim, Al Hafiz Akbar Maulana Siagian, Siti Kania Kushadiani, et al. "Usability and acceptance of crowd-based early warning of harmful algal blooms." PeerJ 11 (March 1, 2023): e14923. http://dx.doi.org/10.7717/peerj.14923.

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Crowdsensing has become an alternative solution to physical sensors and apparatuses. Utilizing citizen science communities is undoubtedly a much cheaper solution. However, similar to other participatory-based applications, the willingness of community members to be actively involved is paramount to the success of implementation. This research investigated factors that affect the continual use intention of a crowd-based early warning system (CBEWS) to mitigate harmful algal blooms (HABs). This study applied the partial least square-structural equation modeling (PLS-SEM) using an augmented technology acceptance model (TAM). In addition to the native TAM variables, such as perceived ease of use and usefulness as well as attitude, other factors, including awareness, social influence, and reward, were also studied. Furthermore, the usability factor was examined, specifically using the System Usability Scale (SUS) score as a determinant. Results showed that usability positively affected the perceived ease of use. Moreover, perceived usefulness and awareness influenced users’ attitudes toward using CBEWS. Meanwhile, the reward had no significant effects on continual use intention.

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Borcherding, Jost. "Ten Years of Practical Experience with the Dreissena-Monitor, a Biological Early Warning System for Continuous Water Quality Monitoring." Hydrobiologia 556, no. 1 (February 2006): 417–26. http://dx.doi.org/10.1007/s10750-005-1203-4.

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Zi, WANG, TANG Yong, FU Yuanyuan, MENG Wei, WANG Shuai, and LIU Xiaolin. "Monitoring of biomass at Cooling Water System of hongyanhe nuclear power plant by using acoustic methods." E3S Web of Conferences 194 (2020): 01007. http://dx.doi.org/10.1051/e3sconf/202019401007.

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In recent years, there have been large-scale jellyfish outbreaks in the Bohai Sea in summer, which have greatly affected the water intake for cold source of Hongyanhe nuclear power station in Fuzhou bay and threatened the normal operation. This study aims at early warning of invasion of jellyfish, designs and develops acoustic monitoring system for cold source biological (jellyfish)by using ascientificechosounder (EY60,70kHz,Simrad), and carries out real-time monitoring of the echo of cold source biological entering water intake, so as to obtain the resource density of jellyfish from June to September 2019. The acoustic data is processed with a software of Echoview to calculate the average SV and detect the strength of the single target to calculate the daily average flux of the monitoring point. According to the monitoring results, the maximum and minimum daily average values of SV were -62.7dB and -80.0dB, respectively. The maximum and minimum daily average values of target strength are -37.2dB and -81.0dB, respectively. The maximum and minimum daily average values of flux are 5.36ind/(s•m2) and 1.2x10-5ind/(s•m2).Combined with the daily cleaning amount of the monitoring point back-end intercepting network and meteorological data, the comparative analysis is carried out to determine the index level of the acoustic warning for cold source biological flowing into the water intake according to the correlation between average flux and amount of cleaned net.

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Osborn, Dan. "The breadth of climate change impacts on biological systems." Emerging Topics in Life Sciences 3, no. 2 (April 30, 2019): 107–13. http://dx.doi.org/10.1042/etls20180114.

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Abstract Human activity is driving climate change. This is affecting and will affect many aspects of life on earth. The breadth of its impacts is very wide and covers human, animal and plant health, and also the planet's biodiversity and the services that deliver benefits to people from natural capital. Finding solutions to the challenge of climate change will require multidisciplinary action in which the life sciences have a major role to play as this issue of Emerging Topics in Life Sciences indicates. More process and mechanistic knowledge could underpin solutions or even provide early warning of impacts. Any solutions will need to be developed and deployed in ways that gain and maintain public support.

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Journal articles on the topic 'Biological Early Warning System'

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