Mathematical approach for predicting non-negative tristimulus values using the CAT02 chromatic adaptation transform

It has been reported that for certain colour samples, the chromatic adaptation transform CAT02 imbedded in the CIECAM02 colour appearance model predicts corresponding colours with negative tristimulus values (TSVs), which can cause problems in certain applications. To overcome this problem, a mathematical approach is proposed for modifying CAT02. This approach combines a non-negativity constraint for the TSVs of corresponding colours with the minimization of the colour differences between those values for the corresponding colours obtained by visual observations and the TSVs of the corresponding colours predicted by the model, which is a constrained non-linear optimization problem. By solving the non-linear optimization problem, a new matrix is found. The performance of the CAT02 transform with various matrices including the original CAT02 matrix, and the new matrix are tested using visual datasets and the optimum colours. Test results show that the CAT02 with the new matrix predicted corresponding colours without negative TSVs for all optimum colours and the colour matching functions of the two CIE standard observers under the test illuminants considered. However, the accuracy with the new matrix for predicting the visual data is approximately 1 CIELAB colour difference unit worse compared with the original CAT02. This indicates that accuracy has to be sacrificed to achieve the non-negativity constraint for the TSVs of the corresponding colours.

Stationarity and regularity of infinite collections of sets. Applications to infinitely constrained optimization

This article continues the investigation of stationarity and regularity properties of infinite collections of sets in a Banach space started in Kruger and López (J. Optim. Theory Appl. 154(2), 2012), and is mainly focused on the application of the stationarity criteria to infinitely constrained optimization problems. We consider several settings of optimization problems which involve (explicitly or implicitly) infinite collections of sets and deduce for them necessary conditions characterizing stationarity in terms of dual space elements—normals and/or subdifferentials.

Calmness modulus of linear semi-infinite programs

Our main goal is to compute or estimate the calmness modulus of the argmin mapping of linear semi-infinite optimization problems under canonical perturbations, i.e., perturbations of the objective function together with continuous perturbations of the right-hand side of the constraint system (with respect to an index ranging in a compact Hausdorff space). Specifically, we provide a lower bound on the calmness modulus for semi-infinite programs with unique optimal solution which turns out to be the exact modulus when the problem is finitely constrained. The relationship between the calmness of the argmin mapping and the same property for the (sub)level set mapping (with respect to the objective function), for semi-infinite programs and without requiring the uniqueness of the nominal solution, is explored, too, providing an upper bound on the calmness modulus of the argmin mapping. When confined to finitely constrained problems, we also provide a computable upper bound as it only relies on the nominal data and parameters, not involving elements in a neighborhood. Illustrative examples are provided.

Spatiotemporal characteristics of the Huangtupo landslide in the Three Gorges region (China) constrained by radar interferometry

The Huangtupo landslide is one of the largest in the Three Gorges region, China. The county-seat town of Badong, located on the south shore between the Xiling and Wu gorges of the Yangtze River, was moved to this unstable slope prior to the construction of the Three Gorges Project, since the new Three Gorges reservoir completely submerged the location of the old city. The instability of the slope is affecting the new town by causing residential safety problems. The Huangtupo landslide provides scientists an opportunity to understand landslide response to fluctuating river water level and heavy rainfall episodes, which is essential to decide upon appropriate remediation measures. Interferometric Synthetic Aperture Radar (InSAR) techniques provide a very useful tool for the study of superficial and spatially variable displacement phenomena. In this paper, three sets of radar data have been processed to investigate the Huangtupo landslide. Results show that maximum displacements are affecting the northwest zone of the slope corresponding to Riverside slumping mass I#. The other main landslide bodies (i.e. Riverside slumping mass II#, Substation landslide and Garden Spot landslide) exhibit a stable behaviour in agreement with in situ data, although some active areas have been recognized in the foot of the Substation landslide and Garden Spot landslide. InSAR has allowed us to study the kinematic behaviour of the landslide and to identify its active boundaries. Furthermore, the analysis of the InSAR displacement time-series has helped recognize the different displacement patterns on the slope and their relationships with various triggering factors. For those persistent scatterers, which exhibit long-term displacements, they can be decomposed into a creep model (controlled by geological conditions) and a superimposed recoverable term (dependent on external factors), which appears closely correlated with reservoir water level changes close to the river's edge. These results, combined with in situ data, provide a comprehensive analysis of the Huangtupo landslide, which is essential for its management.

Characterization of soluble and bound EPS obtained from 2 submerged membrane bioreactors by 3D-EEM and HPSEC

This research study deals with the quantification and characterization of the EPS obtained from two 25 L bench scale membrane bioreactors (MBRs) with micro-(MF-MBR) and ultrafiltration (UF-MBR) submerged membranes. Both reactors were fed with synthetic water and operated for 168 days without sludge extraction, increasing their mixed liquor suspended solid (MLSS) concentration during the experimentation time. The characterization of soluble EPS (EPSs) was achieved by the centrifugation of mixed liquor and bound EPS (EPSb) by extraction using a cationic resin exchange (CER). EPS characterization was carried out by applying the 3-dimensional excitation–emission matrix fluorescence spectroscopy (3D-EEM) and high-performance size exclusion chromatography (HPSEC) with the aim of obtaining structural and functional information thereof. With regard to the 3D-EEM analysis, fluorescence spectra of EPSb and EPSs showed 2 peaks in both MBRs at all the MLSS concentrations studied. The peaks obtained for EPSb were associated to soluble microbial by-product-like (predominantly protein-derived compounds) and to aromatic protein. For EPSs, the peaks were associated with humic and fulvic acids. In both MBRs, the fluorescence intensity (FI) of the peaks increased as MLSS and protein concentrations increased. The FI of the EPSs peaks was much lower than for EPSb. It was verified that the evolution of the FI clearly depends on the concentration of protein and humic acids for EPSb and EPSs, respectively. Chromatographic analysis showed that the intensity of the EPSb peak increased while the concentrations of MLSS did. Additionally, the mean MW calculated was always higher the higher the MLSS concentrations in the reactors. MW was higher for the MF-MBR than for the UF-MBR for the same MLSS concentrations demonstrating that the filtration carried out with a UF membrane lead to retentions of lower MW particles.

Biogas from MSW landfill: Composition and determination of chlorine content with the AOX (adsorbable organically bound halogens) technique

An exhaustive characterization of the biogas from some waste disposal facilities has been carried out. The analysis includes the main components (methane, carbon dioxide, nitrogen and oxygen) as well as trace components such as hydrogen sulphide, ammonia and VOCs (volatile organic compounds) including siloxanes and halogenated compounds. VOCs were measured by GC/MS (Gas Chromatography/Mass Spectrometry) using two different procedures: thermal desorption of the Tenax TA and Carbotrap 349 tubes and SPME (Solid Phase Micro-Extraction). A method has been established to measure the total halogen content of the biogas with the AOX (adsorbable organically bound halogens) technique. The equipment used to analyze the samples was a Total Organic Halogen Analyzer (TOX-100). Similar results were obtained when comparing the TOX (Total Organic Halogen) values with those obtained by GC/MS. The halogen content in all the samples was under 22 mg Cl/Nm3 which is below the limit of 150 mg/Nm3 proposed in the Spanish Regulations for any use of the biogas. The low chlorine content in the biogas studied, as well as the low content of other trace compounds, makes it suitable for use as a fuel for electricity generating engines.

Beyond the H2/CO2 upper bound: one-step crystallization and separation of nano-sized ZIF-11 by centrifugation and its application in mixed matrix membranes

The synthesis of nano-sized ZIF-11 with an average size of 36 ± 6 nm is reported. This material has been named nano-zeolitic imidazolate framework-11 (nZIF-11). It has the same chemical composition and thermal stability and analogous H2 and CO2 adsorption properties to the conventional microcrystalline ZIF-11 (i.e. 1.9 ± 0.9 μm). nZIF-11 has been obtained following the centrifugation route, typically used for solid separation, as a fast new technique (pioneering for MOFs) for obtaining nanomaterials where the temperature, time and rotation speed can easily be controlled. Compared to the traditional synthesis consisting of stirring + separation, the reaction time was lowered from several hours to a few minutes when using this centrifugation synthesis technique. Employing the same reaction time (2, 5 or 10 min), micro-sized ZIF-11 was obtained using the traditional synthesis while nano-scale ZIF-11 was achieved only by using centrifugation synthesis. The small particle size obtained for nZIF-11 allowed the use of the wet MOF sample as a colloidal suspension stable in chloroform. This helped to prepare mixed matrix membranes (MMMs) by direct addition of the membrane polymer (polyimide Matrimid®) to the colloidal suspension, avoiding particle agglomeration resulting from drying. The MMMs were tested for H2/CO2 separation, improving the pure polymer membrane performance, with permeation values of 95.9 Barrer of H2 and a H2/CO2 separation selectivity of 4.4 at 35 °C. When measured at 200 °C, these values increased to 535 Barrer and 9.1.

Constrained self-organizing feature map to preserve feature extraction topology

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.