Comparing in situ particle monitoring to microscopic counts of plankton in a drinking water reservoir

In a one-year study, the multispecies assemblages of phytoplankton (picoplankton to microplankton) within a drinking water reservoir were counted, determined and evaluated in their size fractions using microscope enumeration (MC). The manual counts were compared with the size evaluation obtained by a light obscuring particle counter (PC) in order to evaluate its use for the monitoring practice of a drinking water reservoir. With this multispecies comparison we present a novel approach for the evaluation of automated counting systems.The picoplankton clearly remained uncounted by the PC even though its lower size limits imply an adequate match. The highest and most consistent count numbers of plankton (nano- and microplankton) and particles were obtained during the spring mass development. However, from the middle of the year onwards, the measured particle concentration surpassed the counted plankton abundances by two- to threefold indicating the rise of seston within the water column. This fraction would be missed if counted solely by MC. Further, the PC consistently undersized the biological counts, but not the minerogenic fraction represented by the manganese oxidising bacteria. Consequently, the rise and decline of Metallogenium bacteria was reliably monitored with the PC.The PC provides additional size information compared to other bulk optical sensors (turbidity, chlorophyll-a). The correlation of particles with probe measurement always exceeded the plankton coefficient, but all combinations of plankton, particle and probe measurement revealed significant linear regressions. However, the redundancy of the chlorophyll-a probes was also shown in order to explain plankton abundances.Our results indicate that background knowledge of the monitored system and cautious interpretation of data is required to allocate and understand automated particle counts. Therefore, only in combination with MC, the PC enables phytoplankton or minerogenic particle counts under frequent real-time monitoring conditions. As such it may serve as a helpful tool for example in critical situations in the management of drinking water reservoirs.     

Design of a multichannel, multiresolution smart imaging system

This paper presents the design of a multichannel imaging system where the different optical channels have a different angular resolution and field-of-view. Such an imaging system is able to resolve fine details in a small region of interest through the channel that has the highest angular resolution (0.0096°) while controlling the surrounding region through the channel that has the widest field-of-view (2×40°). An interesting feature of such a multichannel, multiresolution imaging system is that various image processing algorithms can be applied at different segments of the image sensor. We have designed a three channel imaging system where each optical channel consists of four aspheric lens surfaces. These three imaging channels share a single image sensor with a resolution of 1440×960 and a 10 μm pixel size. All imaging channels have diffraction-limited performance ensuring good overall image quality.     

Near-infrared spectroscopy for cocrystal screening. A comparative study with Raman spectroscopy

Near-infrared (NIR) spectroscopy is a well-established technique for solid-state analysis, providing fast, noninvasive measurements. The use of NIR spectroscopy for polymorph screening and the associated advantages have recently been demonstrated. The objective of this work was to evaluate the analytical potential of NIR spectroscopy for cocrystal screening using Raman spectroscopy as a comparative method. Indomethacin was used as the parent molecule, while saccharin and l-aspartic acid were chosen as guest molecules. Molar ratios of 1:1 for each system were subjected to two types of preparative methods. In the case of saccharin, liquid-assisted cogrinding as well as cocrystallization from solution resulted in a stable 1:1 cocrystalline phase termed IND-SAC cocrystal. For l-aspartic acid, the solution-based method resulted in a polymorphic transition of indomethacin into the metastable alpha form retained in a physical mixture with the guest molecule, while liquid-assisted cogrinding did not induce any changes in the crystal lattice. The good chemical peak selectivity of Raman spectroscopy allowed a straightforward interpretation of sample data by analyzing peak positions and comparing to those of pure references. In addition, Raman spectroscopy provided additional information on the crystal structure of the IND-SAC cocrystal. The broad spectral line shapes of NIR spectra make visual interpretation of the spectra difficult, and consequently, multivariate modeling by principal component analysis (PCA) was applied. Successful use of NIR/PCA was possible only through the inclusion of a set of reference mixtures of parent and guest molecules representing possible solid-state outcomes from the cocrystal screening. The practical hurdle related to the need for reference mixtures seems to restrict the applicability of NIR spectroscopy in cocrystal screening.     

Screening for organic phosphorus compounds in aquatic sediments by liquid chromatography coupled to ICP-AES and ESI-MS/MS

The structures of organic phosphorous (P) compounds in aquatic sediments are to a large extent unknown although these compounds are considered to play an important role in regulating lake trophic status. To enhance identification of these compounds, a liquid chromatography (LC) method for their separation was developed. The stationary phase was porous graphitic carbon (PGC), and the mobile phases used in the gradient elution were compatible with both inductive coupled plasma atomic emission spectroscopy (ICP-AES) and electrospray ionization tandem mass spectrometry (ESI-MS/MS). With LC-ICP-AES, eight different P containing peaks could be observed in the P chromatogram indicating that at least eight different P compounds were separated. With the setup of an information dependent acquisition (IDA) with ESI-MS/MS, the mass over charge ( m/ z) of compounds containing a phosphate group (H 2PO 3 (-), m/ z 97) could be measured and further fragmentation experiments gave additional information on the structure of almost 40 separated P compounds, several were verified to be nucleotides. ICP-AES was very suitable in the development of the LC method and allowed screening and quantification of P compounds. The presented LC-ESI-MS/MS technique was able to identify several sediment organic P compounds.     

Multi-objective scheduling problems: Determination of pruned Pareto sets

There are often multiple competing objectives for industrial scheduling and production planning problems. Two practical methods are presented to efficiently identify promising solutions from among a Pareto optimal set for multi-objective scheduling problems. Generally, multi-objective optimization problems can be solved by combining the objectives into a single objective using equivalent cost conversions, utility theory, etc., or by determination of a Pareto optimal set. Pareto optimal sets or representative subsets can be found by using a multi-objective genetic algorithm or by other means. Then, in practice, the decision maker ultimately has to select one solution from this set for system implementation. However, the Pareto optimal set is often large and cumbersome, making the post-Pareto analysis phase potentially difficult, especially as the number of objectives increase. Our research involves the post Pareto analysis phase, and two methods are presented to filter the Pareto optimal set to determine a subset of promising or desirable solutions. The first method is pruning using non-numerical objective function ranking preferences. The second approach involves pruning by using data clustering. The k-means algorithm is used to find clusters of similar solutions in the Pareto optimal set. The clustered data allows the decision maker to have just k general solutions from which to choose. These methods are general, and they are demonstrated using two multi-objective problems involving the scheduling of the bottleneck operation of a printed wiring board manufacturing line and a more general scheduling problem.     

Industrial Knowledge Bases as Drivers of Open Innovation?

The article presents an analysis of a large-scale survey with the aim of understanding differences in the open, interactive and distributed nature of external innovation relations amongst firms belonging to different industrial knowledge bases. The thesis is that the source of critical innovation relevant knowledge differs between industrial knowledge bases, making the character and the need of openness contingent on these specificities. Accordingly, we anticipate that we will observe systematic variations in how industries access and combine innovation-related external knowledge. In our analyses we attempt to address a gap in the literature by examining how industrial knowledge bases affect the recombination of knowledge by analysing the different extents, forms (formal and informal) and geography of inbound open innovation. The article illustrates that features and structures of inbound open innovation align, to a large extent, with the industries' knowledge bases and that there is a interplay between an industry's knowledge base, the internal organisation of innovation processes and the channels and geography of inbound open innovation.     

Characterization of Raman spectra measured in vivo for the detection of cervical dysplasia

Raman spectroscopy has been shown to have the potential for providing differential diagnosis in the cervix with high sensitivity and specificity in previous studies. The research presented here further evaluates the potential of near-infrared Raman spectroscopy to detect cervical dysplasia in a clinical setting. Using a portable system, Raman spectra were collected from the cervix of 79 patients using clinically feasible integration times (5 seconds on most patients). Multiple Raman measurements were taken from colposcopically normal and abnormal areas prior to the excision of tissue. Data were processed to extract Raman spectra from measured signal, which includes fluorescence and noise. The resulting spectra were correlated with the corresponding histopathologic diagnosis to determine empirical differences between different diagnostic categories. Using histology as the gold standard, logistic regression discrimination algorithms were developed to distinguish between normal ectocervix, squamous metaplasia, and high-grade dysplasia using independent training and validation sets of data. An unbiased estimate of the accuracy of the model indicates that Raman spectroscopy can distinguish between high-grade dysplasia and benign tissue with sensitivity of 89% and specificity of 81%, while colposcopy in expert hands was able to discriminate with a sensitivity and specificity of 87% and 72%.