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In this paper, a multi-freedom ski training system is introduced for indoor alpine skiing training and entertainment. The translation platform and the six-degree-of-freedom platform are adopted in the system to realize a wide range of slalom training and terrain simulation. Combining the washout algorithm with the virtual scene and terrain information in Unity3D, the system provides users with the real physical and visual experience of alpine skiing. In the design of washout algorithm, sparrow search algorithm (SSA) is used to optimize the parameters of washout filter, which can achieve a less sensation error and a higher efficiency of the workspace usage. Simulation and experimental results show that our system can give users a real alpine skiing experience, and facilitate the users to ski training and experience the terrain of the ski trail.

Quantitative analysis of sports is an important development direction of scientific skiing training, and the digital expression of human movement patterns during skiing is the basis for scientific quantitative analysis. A human motion capture and attitude reconstruction system based on a wearable BSBD inertial measurement unit was designed and built, combined with the human multi-rigid body motion model to realize the human body reconstruction during the skiing, and applied to the auxiliary training of slewing movements in alpine skiing. At the same time, for the indoor training scene based on the multi-degree-of-freedom simulated ski training platform, a digital evaluation method suitable for ski slalom is proposed. The method uses motion capture system and posture reconstruction system to extract five kinds of sliding characteristic data of skiers, and realizes the evaluation of skiers’ technical parameters through similarity measurement and linear fitting with high-level athletes’ motion parameters, so as to assist scientific training. Finally, experiments are carried out on the indoor Olymp simulated ski training bench to verify the effectiveness of the method.

Space bone loss is the most serious medical problem experienced by astronauts during mid- and long-term flights. Previous reports had shown that miRNAs were associated in bone remodeling and space bone loss. The present study is addressed screening and identify novel miRNAs associated with the skeletal response to gravity changes which play important roles in the regulation of bone formation. Tail-suspension and cell clinorotation were used to simulate microgravity. sRNA deep sequencing, bioinformatics analysis and clone technique were performed to find potential novel gravity-response miRNAs in the bone femur after 28 days’ rat tail-suspension. Six candidate novel miRNAs were selected and analyzed their expression in simulated microgravity and fluid shear stress conditions by quantitative real-time polymerase chain reaction (RT-qPCR). The expression of five novel miRNAs (RN4, RN21, RN43, RN48 and RN50) were changed in tail-suspended rat femurs and clinorotated UMR-106 cells, and up-regulated in UMR-106 after fluid force stress stimulation. Furthermore, The prediction and their enrichment analysis of miRNA targets showed the potential pathways by which RN4, RN43 and RN50 affected osteoblast differentiation and proliferation. Subsequently, we performed and identified the effects of RN4, RN43 and RN50 on the differentiation and proliferation of UMR-106. Taken together, we identified 3 novel miRNAs in bone which may respond to gravity change and regulate osteoblast differentiation or proliferation.

BackgroundAn innovative prone cervical spine surgical position using a body-shape plaster bed with skull traction (BSPST) was compared with the traditional prone surgical position with horseshoe headrests.MethodsA total of 47 patients, undergoing posterior cervical spine surgery for cervical spine fracture, were retrospectively classified into two groups, the BSPST group (n = 24) and the traditional group (n = 23), and underwent a posterior instrumented fusion with or without decompression. Multiple indicators were used to evaluate the advantages of the BSPST compared with the traditional position.ResultsAll the operations went smoothly. The mean recovery rate was 56.30% in the BSPST group and 48.55% in the traditional group (p = 0.454), with no significant difference. The intraoperative blood loss (177.5 ml vs. 439.1 ml, p = 0.003) and the total incidence of complications (8.3 vs. 47.8%, p = 0.004) were significantly less in the BSPST group than in the traditional group. In addition, the BSPST position provided a greater comfort level for the operators and allowed convenient intraoperative radiography.ConclusionsThis is the first study to describe a combined body-shape plaster bed and skull traction as an innovative cervical spine-prone surgical position that is simple, safe, and stable, intraoperative traction direction adjustable, reproducible, and economical for posterior cervical spine fracture surgery, and potentially other cervical and upper dorsal spine surgeries in the prone position. Additionally, this position provides the surgeons with a comfortable surgical field and can be easily achieved in most orthopedic operation rooms.

The core circadian clock gene, Clock, is a positive component of the transcription/translation feedback loop in the master pacemaker suprachiasmatic nucleus (SCN) in mammals. The robust daytime peak of some clock genes in the wild-type SCN is absent in Clock mutant mice. However, very little is known about the impact of Clock mutation on the expression of other functional genes in SCN. Here, we performed cDNA microarray and found 799 differentially expressed genes (DEGs) at zeitgeber time 2 (ZT2) and 1289 DEGs at ZT14 in SCN of Clock△19/△19 mutant mice. KEGG pathway analysis showed that the changed mRNAs were highly associated with hedgehog signaling pathway, retinol metabolism, allograft rejection, drug metabolism, hematopoietic cell lineage and neuroactive ligand-receptor interaction. The top 14 and 71 hub genes were identified from the protein-protein interaction (PPI) network at ZT2 and ZT14, respectively. The sub-networks revealed hub genes were involved in olfactory transduction and neuroactive ligand-receptor interaction pathways. These results demonstrate the Clock△19/△19 mutation alters the expression of various genes involved in a wide spectrum of biological function in mouse SCN, which are helpful for better understanding the function of Clock and potential regulatory mechanisms.

An early warning scheme is proposed that runs ensembles of inferential models for predicting the cyanobacterial population dynamics and cyanotoxin concentrations in drinking water reservoirs on a diel basis driven by in situ sonde water quality data. When the 10- to 30-day-ahead predicted concentrations of cyanobacteria cells or cyanotoxins exceed pre-defined limit values, an early warning automatically activates an action plan considering in-lake control, e.g. intermittent mixing and ad hoc water treatment in water works, respectively. Case studies of the sub-tropical Lake Wivenhoe (Australia) and the Mediterranean Vaal Reservoir (South Africa) demonstrate that ensembles of inferential models developed by the hybrid evolutionary algorithm HEA are capable of up to 30 days forecasts of cyanobacteria and cyanotoxins using data collected in situ . The resulting models for Dolicospermum circinale displayed validity for up to 10 days ahead, whilst concentrations of Cylindrospermopsis raciborskii and microcystins were successfully predicted up to 30 days ahead. Implementing the proposed scheme for drinking water reservoirs enhances current water quality monitoring practices by solely utilising in situ monitoring data, in addition to cyanobacteria and cyanotoxin measurements. Access to routinely measured cyanotoxin data allows for development of models that predict explicitly cyanotoxin concentrations that avoid to inadvertently model and predict non-toxic cyanobacterial strains.

Microgravity has many detrimental impact on brain functions, however the underlying mechanism remain unclear. In present study, 28 days of tail-suspension (30°) was used to simulate microgravity in rats. We showed that oxidative stress in hippocampus was increased after 28 days of simulated microgravity in consideration of the decreased expression of NF-E2-related factor 2 (Nrf2) and the declined activities of total superoxide dismutase (T-SOD), CuZn-SOD, glutathione peroxidase (GSH-PX) and total antioxidant capacity (T-AOC). Using RNA-seq, we further investigated the effect of simulated microgravity on the expression of genes in hippocampus, and 849 genes were found to be differentially expressed. According to pathway analysis, the differentially expressed genes involved in cytoskeleton, metabolism, immunity, transcription regulation, etc. It is interesting to note that the differentially expressed genes were involved in hypoxia-associated pathway. In agreement with this, the expression of hypoxia induced factor-1α (HIF-1α), the master regulator of oxygen homeostasis, was significantly increased. Meanwhile, HIF-2α, a HIF-1α paralog, was elevated compared with the control group. The expression of pyruvate dehydrogenase kinase 1 (PDK1), lactate dehydrogenase A (LDHA) and vascular endothelial growth factor (VEGF), three well-defined downstream targets of HIF-1α, were up-regulated in hippocampus after 28 days of simulated microgravity exposure. Additionally, brain oxygen saturation (SO2) and blood flow analyzed by the tissue oxygen analysis system were also significantly reduced. These findings indicate that simulated microgravity might cause an alteration in oxygen homeostasis, providing novel insight into better understanding of how simulated microgravity affects the function of hippocampus and a new direction to the development of countermeasure for brain dysfunction during spaceflight (actual microgravity).

This paper proposes a novel multi-objective hybrid evolutionary algorithm (MOHEA) that allows spatially-explicit modelling of local outbreaks and dispersal of population density. The MOHEA was tested for modelling at once two cyanobacteria populations at one lake site, same population in two different lakes and same population at three different sites of one lake. All experiments with MOHEA utilized water quality time-series and abundances of Anabaena and Cylindrospermopsis monitored in the sub-tropical Lakes Wivenhoe and Somerset in Queensland (Australia) from 1999 to 2010. Results have demonstrated the capacity of MOHEA to determine generic rules that: (1) reveal crucial thresholds for outbreaks of cyanobacteria blooms, and (2) perform spatially-explicit forecasting of timing and magnitudes 7-day-ahead of bloom events.

Spaceflight leads to health risks including bone demineralization, skeletal muscle atrophy, cardiovascular dysfunction, and disorders of almost all physiologic systems. However, the impacts of microgravity on blood lineage cells and hematopoietic stem cells (HSCs) in vivo are largely unknown. In this study, we analyzed peripheral blood samples from 6 astronauts who had participated in spaceflight missions and found significant changes in several cell populations at different time points. These dynamic alterations of lineage cells and the role of HSCs were further studied in a mouse model, using hindlimb unloading (HU) to simulate microgravity. Large reductions in the frequency of NK cells, B cells, and erythrocyte precursors in the bone marrow of the HU mice were observed, together with an increased frequency of T cells, neutrophils, and HSCs. T cell levels recovered faster than those of B cells and erythrocyte precursors, whereas the recovery rates of NK cells and granulocytes were slow. In addition, competitive reconstitution experiments demonstrated the impaired function of HSCs, although these changes were reversible. Deep sequencing showed changes in the expression of regulatory molecules important for the differentiation of HSCs. This study provides the first determination of altered HSC function under simulated microgravity in vivo. The impairment of HSC function and differentiation provides an explanation for the immune disorders that occur under simulated microgravity. Thus, our findings demonstrated that spaceflight and simulated microgravity disrupt the homeostasis of immune system and cause dynamic alterations on both HSCs and lineage cells.-Cao, D., Song, J., Ling, S., Niu, S., Lu, L., Cui, Z., Li, Y., Hao, S., Zhong, G., Qi, Z., Sun, W., Yuan, X., Li, H., Zhao, D., Jin, X., Liu, C., Wu, X., Kan, G., Cao, H., Kang, Y., Yu, S., Li, Y. Hematopoietic stem cells and lineage cells undergo dynamic alterations under microgravity and recovery conditions.

Circadian locomotor output cycles kaput protein (CLOCK) is a core transcription factor of complex integrated feedback loops in mammalian circadian clock. More genes have been reported to be regulated by CLOCK, however little is known about the role of CLOCK-mediated miRNAs. To dissect this, we used microarray analysis to measure miRNAs expression in suprachiasmatic nuclei (SCN) of wild-type (WT) and ClockΔ19 mutant mice at two different time points. We found that miRNAs regulation in two time points was extensive (nearly 75% of the miRNAs expressed at each time point), and very little overlap, with only six miRNAs in common. Besides this, the predicted CLOCK regulated miRNAs at two time points participated in extremely diverse pathways. We validated nine miRNAs (miR-125a-3p, miR-144, miR-199a-5p, miR-199b*, miR-200a, miR-200b, miR-203, miR-449a, and miR-96), which were involved in the same signaling pathway-hippo signaling pathway. The rhythms of these miRNAs showed a broad distribution of phase, amplitude, and waveform in Clock mutation. And further analysis indicated that there may be three models of miRNA-mediated circadian rhythms and hippo signaling pathway. MiRNA, the small player, may play a hub role in connecting circadian rhythms and other pathways via its multiple target genes networks.

Evolutionary computation has been applied to predict the occurrence of massive cyanobacteria proliferations; in the present study, this tool was further used to explore the factors responsible for maintaining picocyanobacterial dominance. Aiming to increase the understanding of factors that promote dominance of picocyanobacteria in tropical reservoirs, we chose two reservoirs used for water supplies located in different regions of Brazil and subjected to climate changes such as warmer winters that intensify water column stratification and prolonged dry seasons that cause water level decreases. This study focused on the diagnosis of the relationships among picocyanobacteria (1–2 μm), zooplankton and environmental variables using evolutionary computation. The integrated data analysis performed here was very successful in elucidating the dynamics of picocyanobacterial density variation influenced by both abiotic and biotic factors by the modeling approach. Relative water column stability - RWCS and electrical conductivity were highlighted as the most important environmental drivers for picocyanobacterial peaks. Hybrid Evolutionary Analysis (HEA) models for the two reservoirs indicated for the first time in the literature that rotifers, small-sized cladocerans and copepods (mainly nauplii) can directly or indirectly control picocyanobacteria in tropical mesotrophic reservoirs, depending on RWCS conditions and electrical conductivity. However, this control is modulated by pH, water transparency and water temperature thresholds.

Circadian locomotor output cycles kaput protein (CLOCK) is a core transcription factor of complex integrated feedback loops in mammalian circadian clock. More genes have been reported to be regulated by CLOCK, however little is known about the role of CLOCK-mediated miRNAs. To dissect this, we used microarray analysis to measure miRNAs expression in suprachiasmatic nuclei (SCN) of wild-type (WT) and ClockΔ19 mutant mice at two different time points. We found that miRNAs regulation in two time points was extensive (nearly 75% of the miRNAs expressed at each time point), and very little overlap, with only six miRNAs in common. Besides this, the predicted CLOCK regulated miRNAs at two time points participated in extremely diverse pathways. We validated nine miRNAs (miR-125a-3p, miR-144, miR-199a-5p, miR-199b*, miR-200a, miR-200b, miR-203, miR-449a, and miR-96), which were involved in the same signaling pathway-hippo signaling pathway. The rhythms of these miRNAs showed a broad distribution of phase, amplitude, and waveform in Clock mutation. And further analysis indicated that there may be three models of miRNA-mediated circadian rhythms and hippo signaling pathway. MiRNA, the small player, may play a hub role in connecting circadian rhythms and other pathways via its multiple target genes networks.

The present study aimed to determine how the learning and memory gradually change with the prolonged hindlimb unloading (HU) treatment in rats. Different HU durations (7 d, 14 d, 21 d, and 28 d) in Sprague-Dawley (SD) rats were implemented. Cognitive function was assessed using the Morris water maze (MWM) and the shuttle box test. Additionally, parameters about cholinergic activity and oxidative stress were tested. Results showed that longer-than-14 d HU led to the inferior performances in the behavioral tasks. Besides, acetylcholine esterase (AChE) activity, malondialdehyde (MDA) level in brain, reactive oxygen species (ROS), and 8-hydroxy-2-deoxyguanosine (8-OHdG) concentrations of HU rats were significantly increased. Furthermore, choline acetyltransferase (ChAT), superoxide dismutase (SOD), and catalase (CAT) activity in brain were notably attenuated. Most of these effects were more pronounced after longer exposure (21 d and 28 d) to HU, although some indicators had their own characteristics of change. These results indicate that cholinergic dysfunction and oxidative damage were involved in the learning and memory impairments induced by longer-than-14 d HU. Moreover, the negative effects of HU tend to be augmented as the HU duration becomes longer. The results may be helpful to present possible biochemical targets for countermeasures development regarding the memory deficits under extreme environmental conditions.

Forecasting models for Anabaena, Aphanizomenon and Microcystis have been developed for the hypertrophic phase from 1979 to 1990 and the eutrophic phase from 1997 to 2012 of the polymictic Lake Muggelsee by means of the hybrid evolutionary algorithm HEA. Comparisons of limnological parameters of the two phases revealed not only a distinct seasonal extension of N-limitation but also higher water temperatures that rose earlier and lasted longer between spring and autumn from 1997 to 2012. These differences were reflected by threshold conditions and sensitivity functions of the cyanobacteria-specific models evolved by HEA for the two phases. Seven-day-ahead forecasts matched well timings of peaking biomass observed for the three cyanobacteria but partially failed to predict accurate magnitudes, whereby coefficients of determination r 2 ranged between 0.48 and 0.76 for models in Phase I and between 0.42 and 0.69 in Phase II. The threshold conditions of the models quantified ranges of key predictor variables such as water temperature and transparency, concentrations of NO3-N and PO4-P that were symptomatic for sudden outbreaks of high biomass of the three cyanobacteria. Sensitivity functions extracted from 20 best performing models for each of the three cyanobacteria in both phases indicated different abundances between N-fixing Anabaena and Aphanizomenon compared to non-N-fixing Microcystis in response to strengthened N-limitation in Phase II.

Models are proved to be effective instrument for algae bloom prediction and management. The commonly available prediction models are physically based numerical approach or data-driven approach. However, these models are sometimes restricted by the lack of an explicit representation function or by insufficient data. The present research aimed to develop forecasting models that provide early warning on cyanobacteria outbreaks, as well as understand the ecological thresholds and relationships that determine such events, by means of evolutionary computation. The Lake Taihu, which has been suffering from severe cyanobacteria blooms over the last decades due to eutrophication, was taken as study case. Two modelling approaches were used based on water quality data collected from 31 monitoring sites from 2008 to 2012. First, eight sampling sites representing spatially different environmental conditions across Lake Taihu were selected to develop 2-day ahead forecasting models. The resulting models well-matched the timing and magnitude of the observed cyanobacteria dynamics for all eight sites, which was reflected by coefficients of determination (r2) of 0.62 for eastern site 24 being least favourable to cyanobacteria growth and 0.83 for north-western site 6 being most favourable. The sensitivity analyses revealed inhibitory relationships with nitrate at water temperatures greater than 18 °C and excitatory relationships with phosphate at lower water temperatures for most sites, which suggested N-limitation of the lake existed locally in summer and autumn. Second, the aggregated data from all 31 sites were used to develop a generic 2-day ahead forecasting model. When compared with the observed cyanobacteria data of the eight selected sampling sites, the generic model achieved slightly lower coefficients of determination than the site-specific models, with the lowest r2 value for site 24 (0.36) and the highest r2 value for site 6 (0.77). The sensitivity analysis for the generic model revealed a much lower water temperature threshold of 13.01 °C, above which N-limitation for cyanobacteria growth was indicated. Overall, both the spatially-explicit models and the generic model were suitable for early warning of cyanobacteria blooms at most sampling sites, and specified understanding on the environmental conditions that favour cyanobacteria growth across Lake Taihu.

Spaceflight induces muscle atrophy but mechanism is not well understood. Here, we quantified microRNAs (miRNAs) and mRNA shifts of rat soleus in response to microgravity. MiRNAs and mRNA microarray of soleus after tail suspension (TS) for 7 and 14 days were performed followed by target gene and function annotation analysis and qRT-PCR. Relative muscle mass lost by 37.0% in TS-7 but less than 10% in the following three weeks. TS altered 23 miRNAs and 1313 mRNAs with at least 2-fold. QRT-PCR confirmed some of these changes. MiR-214, miR-486-5p and miR-221 continuously decreased. MiR-674 and Let-7e decreased only in TS-7, while miR-320b and miR-187 decreased only in TS-14. But there was no alteration of miR-320 and miR-206 in both time point. For mRNA detection, actn3 (5.1-fold and 13.8-fold) and myh4 (38-fold and 51.6-fold) increased abundantly and a3galt2 decreased. Predicted targeted genes (whyz, ywhaz and SFRP2) of altered miRNAs decreased. GO terms and cellular pathway of these alteration showed enrichment in regulation of muscle metabolism. Integration analysis of the miRNA and mRNA expression profiles confirmed that eleven genes were differently regulated by four miRNAs. This is the first study that showed expression pattern and synergistical regulation of miRNA and mRNA in rat soleus of TS for up to 14 days.

Five years of water quality data from six stations across the mesotrophic and oligomictic Lajes Reservoir (Brazil) were utilized to develop 7-day ahead forecasting models for the picocyanobacteria Cyanodictyon imperfectum, Cyanogranis ferruginea and Synechococcus sp. by means of the hybrid evolutionary algorithm HEA. The data included physical and chemical water quality parameters as well as abundance data of the three picocyanobacteria. Models based on site-specific data of six monitoring stations forecasted population dynamics of Synechococcus with coefficients of determination (r2) between 0.58 for and 0.88, of Cyanodictyon with r2 between 0.5 and 0.89 and of Cyanogranis with r2 between 0.53 and 0.77. Despite phosphorus limiting conditions the sensitivity analysis revealed that the three picocyanobacteria responded much stronger to nitrate rather than to phosphate concentrations throughout the Lajes Reservoir suggesting that cyanobacteria may have adopted the sulphur-for-phosphorus strategy by utilizing sulfolipids instead. Cyanogranis displayed a negative relationship with increasing water temperature indicating its higher competitiveness at internal nutrient supply and low light levels during winter turnover. The resulting models will inform operational intervention and prevention of fast growth and dispersal of picocyanobacteria in Lajes Reservoir, and reveal environmental thresholds for outbreaks of such events.

This chapter introduces the design and applications of evolutionary algorithms and regression trees for inferential modelling of complex ecological data. Evolutionary algorithms prove to be superior tools for developing short-term forecasting models, revealing ecological thresholds and supporting quantitative meta-analyses as demonstrated exemplarily by means of the hybrid evolutionary algorithm (HEA). A case study of Lake Muggelsee (Germany) illustrates that models developed by HEA enable one to identify ecological thresholds and driving forces that perform short-term forecasting of population growth. The meta-analysis of Lakes Wivenhoe (Australia) and Lake Paranoa (Brazil) exemplifies the capability of models developed by HEA to test hypotheses on forcing functions of population growth across different environmental and climate conditions. Regression trees display fully transparent correlations between habitat properties and ecological entities. The tree induction process does not require prior assumptions, is fast and is not influenced by redundant variables and noise. Case studies for Lake Prespa (Macedonia) and land areas in Victoria (Australia) illustrate the capacity of regression trees to unravel complex ecological relationships.

This study addresses the need for operational models in view of rapidly advancing in situ sensor technology that puts lakes into online surveillance mode. A model ensemble for simulating plankton community dynamics in Lake Kinneret (Israel) from 1988 to 1999 has been induced from electronically-measurable predictor variables (EMPV) such as water temperature, pH, turbidity, electrical conductivity and dissolved oxygen by the hybrid evolutionary algorithm HEA. It cascade wise predicts the total nitrogen to total phosphorus ratios TN/TP, concentrations of chlorophyta, baccilariophyta, cyanophyta and dinophyta, as well as densities of rotifera, cladocera and copepoda solely from EMPV. The best coefficients of determination (r2) have been achieved with 0.6 by the dinophyta model, 0.45 by the rotifera model and 0.44 by the bacillariophyta model. The worst coefficients of determination (r2) have been produced by the cladocera model with 0.24 and by the TN/TP model with 0.28. Despite the differences in the r2 values and apart from the cladocera model, the remaining models matched reasonably well seasonal and interannual plankton dynamics observed over 11 years in Lake Kinneret.The model ensemble developed by HEA also revealed ecological thresholds and relationships determining plankton community dynamics in Lake Kinneret solely based on in situ predictor variables. Predictive model ensemble solely induced from in situ predictor variables by evolutionary computation.Model ensemble predicts 12 years of plankton community dynamics in Lake Kinneret.Model ensemble exemplary for lake models operated for early warning in real-time mode by on-line water quality data.Sensitivity analyses reveal ecological relationships and thresholds determining plankton community dynamics in Lake Kinneret.

Identification of thresholds as indicators for sudden shifts in the community composition has proven difficult. Evolutionary computation learns inferential models from data. We investigated the hypothesis that models built from data of largely different lakes by evolutionary computation reveal similar thresholds for outbreaks of cyanobacteria densities. Here we show that IF–THEN–ELSE models inferred by the hybrid evolutionary algorithm HEA from multidimensional data of the hypertrophic polymictic Lake Taihu (China) and the mesotrophic warm-monomictic Lake Kinneret (Israel) perform fairly good 5-day-ahead forecasting of density outbreaks and indicate thresholds referring to the same environmental factors, such as nitrate and water temperature. The discovered thresholds suggest that hypereutrophic lakes may reach N-limitation at nitrate concentrations that are orders of magnitude higher than in a mesotrophic lake, and that cyanobacteria may grow at much lower water temperatures and within a much wider temperature range at phosphorus sufficiency in a hypereutrophic lake than under phosphorus deficiency in a stratified mesotrophic lake.

Seven-day-ahead forecasting models of Cylindrospermopsis raciborskii in three warm-monomictic and mesotrophic reservoirs in south-east Queensland have been developed by means of water quality data from 1999 to 2010 and the hybrid evolutionary algorithm HEA. Resulting models using all measured variables as inputs as well as models using electronically measurable variables only as inputs forecasted accurately timing of overgrowth of C. raciborskii and matched well high and low magnitudes of observed bloom events with 0.45 ≤ r2 > 0.61 and 0.4 ≤ r2 > 0.57, respectively. The models also revealed relationships and thresholds triggering bloom events that provide valuable information on synergism between water quality conditions and population dynamics of C. raciborskii. Best performing models based on using all measured variables as inputs indicated electrical conductivity (EC) within the range of 206–280 mS m−1 as threshold above which fast growth and high abundances of C. raciborskii have been observed for the three lakes. Best models based on electronically measurable variables for the Lakes Wivenhoe and Somerset indicated a water temperature (WT) range of 25.5–32.7 °C within which fast growth and high abundances of C. raciborskii can be expected. By contrast the model for Lake Samsonvale highlighted a turbidity (TURB) level of 4.8 NTU as indicator for mass developments of C. raciborskii. Experiments with online measured water quality data of the Lake Wivenhoe from 2007 to 2010 resulted in predictive models with 0.61 ≤ r2 > 0.65 whereby again similar levels of EC and WT have been discovered as thresholds for outgrowth of C. raciborskii. The highest validity of r2 = 0.75 for an in situ data-based model has been achieved after considering time lags for EC by 7 days and dissolved oxygen by 1 day. These time lags have been discovered by a systematic screening of all possible combinations of time lags between 0 and 10 days for all electronically measurable variables. The so-developed model performs seven-day-ahead forecasts and is currently implemented and tested for early warning of C. raciborskii blooms in the Wivenhoe reservoir.