Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess

Advances in industrial digital technologies have led to an increasing volume of data generated from industrial bioprocesses, which can be utilised within data-driven models (DDM). However, data volume and variability complications make developing models that captures the underlying biological nature of the bioprocesses challenging. In this study, a framework for developing data-driven models of bioprocesses is proposed and evaluated by modelling an industrial bioprocess, which treats industrial or agrifood wastewaters whilst simultaneously generating bioenergy. Six models were developed to predict the reduction in chemical oxygen demand from the wastewater by the bioprocess and statistically evaluated using both testing data (randomly partitioned data from the model development) and unseen data (new data not used during the model development). The statistical error metrics employed were the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The stacked neural network model was best able to model the bioprocess, having the highest accuracy on the testing data (R2: 0.98; RMSE: 1.29; MAE: 2.27; MAPE: 4.08) and the unseen data (R2: 0.82; RMSE: 2.57; MAE: 1.75; MAPE: 3.68). Data visualisation is used to observe (or confirm) whether new data points are within the model boundaries, helping to increase confidence in the model’s predictions on future data

Multiple target data-driven models to enable sustainable process manufacturing: An industrial bioprocess case study

Process manufacturing industries constantly strive to make their processes increasingly sustainable from an environmental and economic perspective. A manufacturing system model is a powerful tool to holistically evaluate various manufacturing configurations to determine the most sustainable one. Previously models of process manufacturing systems are typically single target models, trained to fit and/or predict data for a single output variable. However, process manufacturing systems produce a variety of outputs with multiple, sometimes contradictory, sustainability implications. These systems require multiple target models to find the most sustainable manufacturing configuration which considers all outputs. A novel bioprocess that treats process wastewaters to reduce pollutant load for reuse, while simultaneously generating energy in the form of biogas was studied. Multiple target models were developed to predict the percentage removal of chemical oxygen demand and total suspended solids, in addition to the biogas (as volume of methane) produced. Predictions from the models were able to reduce wastewater treatment costs by 17.0%. Eight models were developed and statistically evaluated by the coefficient of determination (R2), normalised root mean square error (nRMSE) and mean absolute percentage error (MAPE). An artificial neural network model built following the ensemble of regressor chains demonstrated the best multi target model performance, averaged across all the bioprocess’s outputs (R2 of 0.99, nRMSE of 0.02, MAPE of 1.74). The model is able to react to new regulations and legislation and/or variations in company, sector, world circumstances to provide the most up to date sustainable manufacturing configuration

Visual Lateralization in Wild Striped Dolphins (Stenella coeruleoalba) in Response to Stimuli with Different Degrees of Familiarity

Background: Apart from findings on both functional and motor asymmetries in captive aquatic mammals, only few studies have focused on lateralized behaviour of these species in the wild. Methodology/Principal Findings: In this study we focused on lateralized visual behaviour by presenting wild striped dolphins with objects of different degrees of familiarity (fish, ball, toy). Surveys were conducted in the Gulf of Taranto, the northern Ionian Sea portion delimited by the Italian regions of Calabria, Basilicata and Apulia. After sighting striped dolphins from a research vessel, different stimuli were presented in a random order by a telescopic bar connected to the prow of the boat. The preferential use of the right/left monocular viewing during inspection of the stimuli was analysed. Conclusion: Results clearly showed a monocular viewing preference with respect to the type of the stimulus employed. Due to the complete decussation of the optical nerves in dolphin brain our results reflected a different specialization of brain hemispheres for visual scanning processes confirming that in this species different stimuli evoked different patterns of eye use. A preferential use of the right eye (left hemisphere) during visual inspection of unfamiliar targets was observed supporting the hypothesis that, in dolphins, the organization of the functional neural structures which reflected cerebral asymmetries for visual object recognition could have been subjected to a deviation from the evolutionary line of mos

The EOD Sound Response in Weakly Electric Fish

1. A spontaneous EOD response to sound is described in two gymnotoids of the pulse Electric Organ Discharge (EOD) type, Hypopomus and Gymnotus, and in one mormyrid, Brienomyrus (Figs. 2-4). 2. In all three species, the EOD response to the sound onset was a transient EOD rate increase. In the low EOD rate Hypopomus (3-6 EODs/s at rest) the first, second, or third EOD interval following sound onset was significantly shorter than the average EOD interval before stimulation. The shortest latency found was 100 ms, the longest ca. 1.2 s. Gymnotus (around 50 EODs/s at rest) responded similarly, but the third interval after sound onset was the first to be affected even at highest intensities (shortest latencies approx. 60 ms; latencies >0.5 s at low sound intensities). In Brienomyrus (4-8 EODs/s at rest) the response occurred already at the first EOD interval after sound onset. 3. An EOD sound response was recorded in Hypoporous and in Gymnotus up to 5,000 Hz sound frequency (in one Gymnotus individual: up to 7,000 Hz). Due to technical limitations the low frequency limit of the response could not be exactly determined: the fishes responded well even below 100 Hz. Hypopomus had its maximum sensitivity around 500 Hz (Fig. 5), Gymnotus around 1,000 Hz (Fig. 6). 4. In all three species the EOD sound response was graded with sound intensity (Hypopomus: Fig. 7). 5. No EOD response to sound was found in two gymnotoids of the wave type, Eigenmannia and Apteronotus, and in the gymnotoid pulse fish Rhamphichthys. A criterion is proposed by which it should be possible to predict whether or not a weakly electric fish species will show the EOD sound response. 6. It is concluded that the EOD response to sound is similar to EOD responses to other kinds of stimulation (light, touch, vibration, food, and even electrical). The possible biological function is discussed

Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems

The increasing availability of data, due to the adoption of low-cost industrial internet of things technologies, coupled with increasing processing power from cloud computing, is fuelling increase use of data-driven models in manufacturing. Utilising case studies from the food and drink industry and waste management industry, the considerations and challenges faced when developing data-driven models for manufacturing systems are explored. Ensuring a high-quality set of model development data that accurately represents the manufacturing system is key to the successful development of a data-driven model. The cross-industry standard process for data mining (CRISP-DM) framework is used to provide a reference at to what stage process manufacturers will face unique considerations and challenges when developing a data-driven model. This paper then explores how data-driven models can be utilised to characterise process streams and support the implementation of the circular economy principals, process resilience and waste valorisation

Allopatric differentiation in the acoustic communication of a weakly electric fish from southern Africa, Marcusenius macrolepidotus (Mormyridae, Teleostei)

A few species of the weakly electric snoutfish, the African freshwater family Mormyridae, have been reported to vocalise. However, allopatric populations of a single species were never compared. Members of three allopatric Marcusenius macrolepidotus populations, originating from the Upper Zambezi River in Namibia, the Buzi River (Mozambique), and the Incomati River system in South Africa, vocalised with pulsatile growl- and tonal hoot sounds in dyadic confrontation experiments. A high rate of growling accompanied territorial and agonistic interactions and also non-threatening interactions between males and females, which in one pair appeared to be courtship. Growl sound characteristics of M. macrolepidotus from the Incomati system differed from those of the Upper Zambezi in a significantly higher frequency of the first harmonic (mean, 355 Hz vs 266 Hz). The two vocalising males from the Buzi River generated growls about twice as long as the other fish. Furthermore, the growl pulse period was about 4 ms in M. macrolepidotus from the Upper Zambezi River and from the Incomati system, but 6 ms in M. macrolepidotus from the Buzi River. Hoots were only observed in agonistic encounters. Hoot oscillograms showed a sinusoidal waveform, and the mean duration of this sound was similar in Incomati system fish (mean, 161 ms), Upper Zambezi fish (172 ms) and Buzi fish (103 and 145 ms for the two vocalising individuals). The mean frequency of the first hoot harmonic was higher in Incomati system fish (326 Hz) than in Upper Zambezi fish (245 Hz). Both growl and hoot occurred only in the presence of conspecifics, probably signalling the presence and condition of an opponent, territory owner or potential mate. This is the first evidence for (1) sound production and acoustical communication in another species and genus, M. macrolepidotus, from southern Africa to be (2) geographically differentiated