Assessment of microalgae viability employing insulator-based dielectrophoresis

Microscale bioparticle analysis has advanced significantly providing advantages over bench-scale studies such as the use of a reduced amount of sample and reagents, higher sensitivity, faster response, and portability. Insulator-based dielectrophoresis (iDEP) is a microscale technique where particles are driven by polarization effects under a non-uniform electrical field created by the inclusion of insulators between two electrodes. iDEP possesses attractive advantages over traditional electrode-based dielectrophoresis since there is no electrode degradation and manufacture of the device is simpler and economical. This novel and powerful technique has been applied successfully in the manipulation of macromolecules and cells. In this study, differences in dielectric properties (cell membrane conductivity) of viable and non-viable microalgae, Selenastrum capricornutum, were employed to concentrate and separate a mixture of live and dead cells. A microchannel, manufactured in glass and containing an array of cylindrical insulating posts, was employed to dielectrophoretically immobilize and concentrate the mixture of cells employing direct current electric fields. Experiments showed that live cells exhibited a stronger dielectrophoretic response than dead cells, which allowed cell differentiation. Separation and enrichment of viable and non-viable microalgae was achieved in 35 s with a concentration yield of 10.36 and 15.87 times the initial cell concentration, respectively. These results demonstrate the use of iDEP as a technique for rapid assessment of microalgae viability; unveiling the potential of this powerful technique for environmental applications on lab-on-a-chip platforms.     

Remote sensing of benthic microalgal biomass with a tower-mounted multispectral scanner

A remote sensing instrument was mounted on a 50-ft tower overlooking North Inlet Estuary, South Carolina in order to conduct a remote sensing study of benthic microalgae. The instrument was programmed to take multispectral imagery data along a 90° horizontal frame in six spectral bands ranging from 400–1050 nm and had a ground resolution of about 3 cm. Imagery measurements were encoded in digital form on magnetic tape and were stored, decoded, and manipulated by computer. Correlation coefficients were calculated on imagery data and chlorophyll α concentrations derived from ground truth data. The most significant correlation occurred in the blue spectral band with numerical values ranging from ?0.81 to ?0.88 for three separate sampling periods. Mean values of chlorophyll α for a larger section of mudflat were estimated using regression equations. The scanner has provided encouraging results and promises to be a useful tool in sampling the biomass of intertidal benthic microalgae.     

Separating two species of microalgae in photobioreactors in minimal time

This paper proposes a strategy to separate two strains of microalgae in minimal time. The control is the dilution rate of the continuous photobioreactor. The microalgae dynamics is described by the Droop’s model, taking into account the internal quota storage of the cells. Using Pontryagin’s principle, we develop a dilution-based control strategy that leads to the most efficient species separation in minimal time. A numerical optimal synthesis –based on direct optimization methods– is performed throughout the paper, in order to determine the structure of the optimal feedback-control law, which is bang-singular. Our numerical study reveals that singular arcs play a key role in the optimization problem since they allow the optimal solution to be close to an associated static optimal control problem. A resulting turnpike-like behavior, which characterizes the optimal solution, is highlighted throughout this work.     

Getting the most out of it: Optimal experiments for parameter estimation of microalgae growth models

Mathematical models are expected to play a pivotal role for driving microalgal production towards a profitable process of renewable energy generation. To render models of microalgae growth useful tools for prediction and process optimization, reliable parameters need to be provided. This reliability implies a careful design of experiments that can be exploited for parameter estimation. In this paper, we provide guidelines for the design of experiments with high informative content based on optimal experiment techniques to attain an accurate parameter estimation. We study a real experimental device devoted to evaluate the effect of temperature and light on microalgae growth. On the basis of a mathematical model of the experimental system, the optimal experiment design problem was formulated and solved with both static (constant light and temperature) and dynamic (time varying light and temperature) approaches. Simulation results indicated that the optimal experiment design allows for a more accurate parameter estimation than that provided by the existing experimental protocol. For its efficacy in terms of the maximum likelihood properties and its practical aspects of implementation, the dynamic approach is recommended over the static approach.     

Effects of chlorophyll fluorescence on the estimation of microphytobenthos biomass using spectral reflectance indices

The communities of benthic microalgae that form dense biofilms at the surface of aquatic sediments, or microphytobenthos, are important primary producers in estuarine intertidal flats and shallow coastal waters. The microalgal biomass present in the photic zone of the sediment is a key parameter for ecological and photophysiological studies on microphytobenthos, and has been routinely estimated using hyperspectral reflectance indices based on the chlorophyll (Chl) a red absorption peak at 675 nm, usually the Normalised Difference Vegetation Index (NDVI). This study reports that red region-based biomass indices measured on microphytobenthos biofilms can be significantly affected by the enrichment of reflected light with solar-induced Chl fluorescence emitted by the microalgae. Chl fluorescence emission peaks at 683 nm, counterbalancing the decrease in reflectance centered at 675 nm, thus causing the underestimation of NDVI. The interference of Chl fluorescence was found to be easily identified by a conspicuous double-peak feature in the 670-700 nm region of the second-derivative reflectance spectra. The fluorescence-induced NDVI underestimation was shown to be most pronounced for high surface biomass levels and low incident solar irradiance. Particular aspects of microphytobenthos biofilms, such as the increase in surface Chl fluorescence due the contribution of emission by subsurface layers, and vertical migratory responses by motile microalgae to changes in ambient light, further complicate the effects on biomass estimation using NDVI-like indices. By comparing NDVI with a fluorescence-independent biomass index for a wide range of natural light conditions, it was found that Chl fluorescence interference may cause the underestimation of microalgal biomass to reach over 25%, with errors above 10% being expected for more than half of the measuring occasions. These results indicate that the use of NDVI may compromise the correct assessment of important aspects of microphytobenthos ecology, such as the characterisation of migratory behaviour or the determination of biomass-specific productivity rates, and call for the use of alternative biomass indices, not based on the Chl a red absorption peak.     

Change detection using remote sensing in a reef environment of the UAE during the extreme event of El Niño 2015–2016

ABSTRACT

Coral reefs of the United Arab Emirates (UAE) are living in the world’s hottest sea. Recently, corals harbouring Symbiodinium thermophilum, a thermotolerant microalgae, were found to be prevalent among UAE reefs and were reported to endure extreme sea-surface temperatures. Late 2015–early 2016 was marked with the strongest El Niño on record worldwide, which caused massive coral bleaching (loss of symbiotic microalgae from reef-building corals). In September 2015, the waters flanking UAE coasts were identified to be among the areas facing a thermal stress reaching its highest level liable to cause massive coral bleaching. However, the effect of this thermal stress on UAE corals remained largely unknown. Here, multi-temporal DubaiSat-2 satellite images were used to show that changes in the reef environment of Dalma Island, UAE, between 2014 and 2016, occurred in macroalgae-dominant habitats, whereas live corals remained unaltered. Furthermore, extending the study to a larger area helped in discovering a continuum of live and pristine corals, which was not reported or studied before. While sea-surface temperature anomalies of 1°C were reported to significantly damage coral reefs around the world, the live coral habitat was observed to exhibit no-change despite four consecutive months of +2°C to 3°C anomalies reported during the study period. These findings point to the tolerance of UAE live corals faced with extreme climate conditions.     

Adaptive control of light attenuation for optimizing microalgae production

The light attenuation factor, defined by the ratio between the incident light and the light at the bottom of the reactor, is a key operating parameter for light-limited phototrophic culture. Here, two nonlinear control laws have been proposed in order to regulate this ratio: a static controller, which is input-to-state stable with respect to measurement noise, and an adaptive controller. Then, we propose a set-point for the light attenuation factor in order to optimize microalgae productivity under constant illumination. Finally, numerical simulations illustrate how the adaptive controller can be used to optimize biomass productivity under realistic day–night cycles.     

Artificial algae algorithm (AAA) for nonlinear global optimization

In this study, a novel bio-inspired metaheuristic optimization algorithm called artificial algae algorithm (AAA) inspired by the living behaviors of microalgae, photosynthetic species, is introduced. The algorithm is based on evolutionary process, adaptation process and the movement of microalgae. The performance of the algorithm has been verified on various benchmark functions and a real-world design optimization problem. The CEC’05 function set was employed as benchmark functions and the test results were compared with the algorithms of Artificial Bee Colony (ABC), Bee Algorithm (BA), Differential Evolution (DE), Ant Colony Optimization for continuous domain (ACO_R) and Harmony Search (HS_POP). The pressure vessel design optimization problem, which is one of the widely used optimization problems, was used as a sample real-world design optimization problem to test the algorithm. In order to compare the results on the mentioned problem, the methods including ABC and Standard PSO (SPSO2011) were used. Mean, best, standard deviation values and convergence curves were employed for the analyses of performance. Furthermore, mean square error (MSE), root mean square error (RMSE) and mean absolute percentage error (MAPE), which are computed as a result of using the errors of algorithms on functions, were used for the general performance comparison. AAA produced successful and balanced results over different dimensions of the benchmark functions. It is a consistent algorithm having balanced search qualifications. Because of the contribution of adaptation and evolutionary process, semi-random selection employed while choosing the source of light in order to avoid local minima, and balancing of helical movement methods each other. Moreover, in tested real-world application AAA produced consistent results and it is a stable algorithm.     

Optimal control of sustainable development in the biological rehabilitation of the Azov Sea

The article is devoted to the application of the concept of sustainable development management to the task of combating the eutrophication of shallow water bodies (by the example of the Azov Sea). To describe the state dynamics of the water body, partial differential equations solved numerically by the finite difference method have been used. The dynamic problem of minimizing costs for the maintenance of the ecosystem of the water body in the defined condition, which is interpreted as the requirement for sustainable development, has been solved. The research and forecast complex, including the mathematical models of the hydrobiology of the shallow water body, environmental databases, and program library used to design scenarios of the ecological situation in the Azov Sea, has been worked out. Changes in the concentration of malicious blue-green algae due to water pollution by biogenic substances causing the rapid growth of these algae have been forecast. The influence of the spatial distribution of the temperature and the salinity on the biological treatment of the Azov Sea though the introduction of green algae, which displaced the toxic blue-green algae, has been studied. Using the designed research and forecast complex based on the materials of expeditions it is possible to investigate the key mechanisms of formation of vertical and horizontal zones in the distribution of biogenic substances, oxygen, and planktonic populations, to set the values of the parameters for management of the amount of hydrogen sulfide and hypoxemic zones, to evaluate the possibility of the biological treatment of the Azov Sea waters with the help of the introduction of the green alga Chlorella vulgaris BIN, followed by displacement of the toxic blue-algae that are most common in shallow water bodies such as Aphanizomenon flosaquae, and to rank the ecological efficiency of the factors for the management of the stability of the composition of the phytoplankton species, including the blooming of microalgae. Examples of the numerical calculations have been provided. The obtained results have been analyzed.     

Exploiting meteorological forecasts for the optimal operation of algal ponds

Biofuel production from microalgae requires optimizing the operation of cultivation systems (i.e. outdoor raceway ponds) for this process to be economically sustainable. Controlling algal ponds is complex as the cultivation systems are exposed to fluctuating conditions. The strategy investigated in this study uses weather forecasts coupled to a predictive model of algal productivity to optimize pond operation. Productivity was optimized by dynamically controlling rates of fresh medium injection and culture removal into and from the pond. This optimization strategy when applied to a cultivation plant in Nice, South of France, increases the productivity by 2.13 compared to the reference case where the pond depth and dilution rate were kept constant over time. The underlying Model Predictive Control consists of playing with raceway pond thermal inertia and supplying of fresh water to reach rapidly optimal temperature, and then keep a balance between photosynthesis and respiration in the darkest layers of the raceway pond. The meteorological inaccuracy for forecasts beyond 24 h was compensated by frequent updates of the optimal control problem. Finally, this scheme turned out to be robust to inaccurate weather forecasts, and the net productivity value reached was close to the productivity obtained for perfectly known meteorology.     

Mapping microphytobenthos biomass by non-linear inversion of visible-infrared hyperspectral images

This study presents an innovative approach to map microphytobenthos biomass and fractional cover in Bourgneuf Bay (French Atlantic coast) using Digital Airborne Imaging Spectrometer (DAIS) hyperspectral data. Microphytobenthos is a microalgae forming a biofilm on the mudflat. Its spatial distribution is heterogeneous so it varies on a finer scale than that of airborne instrument spatial resolution, leading to a “mixed pixel” problem. Moreover, some microphytobenthic species form, at low tide, a biofilm deposited at the surface of the sediment substrate. The resulting signal is a highly non-linear combination of spectral endmembers due to microscale intimate mixtures. This prevents the use of classical linear unmixing models to retrieve biomass from reflectance spectra. A Modified Gaussian Model (MGM) is therefore used to remove the effects of surface roughness, shadowing and any other unknown processes that contribute to the overall shape (continuum) of the reflectance spectra. Then, relationships between microphytobenthos biomass and spectral shapes are derived from a spectral database compiled from laboratory reflectance spectra of microalgal monospecific cultures with different biomasses. Finally, microphytobenthos biomass and fractional cover are retrieved from the DAIS image by comparing the reflectance spectra of each pixel to a library of synthetic spectra corresponding to combinations of various biomasses and substrate percent cover. This new approach, when compared to more classically used ones such as indices, linear unmixing or spectral distance analysis, is proven to enable a much more reliable determination of biomass despite the large variety of substrates found in Bourgneuf Bay.     

Bidirectional reflectance of coral growth-forms

In situ spectral reflectance measurements of substrates in a coral reef are often obtained by viewing a substrate at nadir. However, it is likely that off-nadir oblique viewing would show different spectral characteristics for most coral reef substrates and provide valuable information on structural properties. To understand the relationship between substrate structure and spectral response, this study examined the bidirectional reflectance distribution function (BRDF) of various growth-forms of hard corals and algae, as well as rock, rubble, and sand. BRDF measurements were collected on Heron Reef, the Great Barrier Reef, Australia, during the spring (October to November) of 2010, using a visible and near-infrared (VNIR) spectroradiometer attached to a goniometer. The measurements were made in the same five view zenith angles as the PROBA-1 Compact High Resolution Imaging Spectrometer (CHRIS) satellite (+55°, +36°, 0°, ?36°, ?55°) in the solar principal plane (SPP). A correction algorithm was used to remove both water column and water surface effects. Uncorrected measurements for sand covered with benthic microalgae appeared to have BRDF effects, but when corrected showed an essentially diffuse spectral response. Corrected measurements for branching corals showed BRDF effects dependent on branch spacing, branch length, and colour. The results indicate that spectral reflectance does vary with view angle for complex substrates such as caespitose corals, macroalgae, and irregular beach-rock and to a lesser extent for digitate corals and rippled sand and that the morphology of the coral and the shadowing between branches determines total spectral response. It is concluded that BRDF information can provide additional discriminating features for some coral reef substrates, particularly in the wavelength range of 550–650 nm.     

基于机器学习的PM2.5短期浓度动态预报模型

针对目前现有的PM2.5模式预报系统的预报值偏离实际浓度较大的问题,从上海市浦东气象局获得2015年2月至7月的PM2.5实况观测浓度、PM2.5模式预报（WRF-Chem）浓度和5个主要气象因子的模式预报数据资料,联合应用支持向量机（SVM）和粒子群优化（PSO）算法建立滚动预报模型,对PM2.5未来24小时浓度进行预报,同时对未来一天的昼、夜均值及日均值浓度进行预报,并与径向基函数神经网络（RBFNN）、多元线性回归法（MLR）、模式预报（WRF-Chem）作对比。实验结果表明,相比其他预报方法,所提出的SVM模型较大提高了PM2.5未来1小时浓度预报精度,这与此前的研究结论相符;所提模型能对PM2.5未来24小时浓度进行较好的预报,能对未来一天的昼均值、夜均值及日均值进行有效预报,并且对未来12小时的逐时浓度及未来一天的夜均值浓度的预报准确度较高。     

尾矿浆浓度与超声波衰减系数的关系研究

针对目前基于超声波法的尾矿浆浓度测量方法没有直接表达浓度与散射衰减系数、黏滞衰减系数的相关关系的问题,采用数值计算方法,研究了超声波在尾矿浆中的衰减特性,得到了声波衰减系数与浓度的相关关系,并通过实验数据的分析论证了数值计算的准确性。研究结果表明:浓度在10%以内时,浓度越大,声速越小;浓度在5%以内时,超声波的衰减系数与浓度近似成正比关系;当超声波频率、粒径一定,浓度在10%以内时,浓度越大,超声波的衰减系数越大。研究结果为超声波在尾矿浆浓度在线监测中的实际应用提供了依据。     

矿井局部通风机智能控制系统的设计

针对传统的矿井局部通风机变频控制系统仅随瓦斯浓度调节风量而存在的不足,文章提出了一种兼顾瓦斯浓度和煤尘浓度的矿井局部通风机智能控制系统的设计方案,介绍了基于模糊PID控制的瓦斯、煤尘浓度的模糊控制器的设计。通过对瓦斯浓度模糊控制器以及煤尘浓度模糊控制器的仿真可以看出,随着工作面瓦斯和煤尘浓度的不同,该智能控制系统会根据爆炸性气体的浓度变化,自动、连续、实时地对局部通风机进行调速。     

富营养化水体环境中COD浓度遥感监测系统设计

对富营养化水体环境中COD浓度进行遥感监测,可以预防富营养化水体环境中COD浓度增加,提高水体水质,增加水循环次数,减少水体中有机物的污染;当前富营养化水体环境中COD浓度遥感监测系统设计方法,以Modis遥感影像数据为原理,依据富营养化水体环境中COD浓度的特征提取结果,对富营养化水体环境中COD浓度进行遥感监测,没有具体对遥感监测系统进行详细地设计,无法获取富营养化水体环境中COD浓度高精度的遥感监测信息,存在遥感监测结果偏差大的问题;提出了一种基于Zigbee的富营养化水体环境中COD浓度遥感监测系统设计方法;该方法先对Zigbee的富营养化水体环境中COD浓度遥感监测系统进行硬件设计,采用IMF对富营养化水体环境中COD浓度进行特征提取,以特征提取结果为基础,依据COD浓度指数时间序列实现富营养化水体环境中COD浓度遥感监测,最后利用Retinex法对COD浓度遥感监测的图像进行处理,完成对富营养化水体环境中COD浓度的遥感监测;仿真实验结果证明,所提系统设计方法可以精确地对富营养化水体环境中COD浓度进行安全快速的遥感监测。     

太湖水体叶绿素浓度与反射光谱特征关系的研究

根据2004年10月在太湖实测的水体反射光谱及实验室分析得到的叶绿素浓度数据,对太湖水体反射光谱特征与叶绿素浓度之间的关系进行探讨与分析。研究结果表明:水体叶绿素浓度与各波长处的反射光谱相关性不大,但是反射光谱经过比值法和微分处理后,两者具有很好的相关性,而且叶绿素浓度与反射光谱700nm附近波峰几何形态特征(波峰位置、面积、净高度)相关性很好,建立太湖水体叶绿素浓度估算模型。