Excited-state dynamics of carotenoids in light-harvesting complexes. 1. Exploring the relationship between the S1 and S* states

Dispersed transient absorption spectra collected at variable excitation intensities in combination with time-resolved signals were used to explore the underlying connectivity of the electronic excited-state manifold of the carotenoid rhodopin glucoside in the light-harvesting 2 complex isolated from Rhodopseudomonas acidophila. We find that the S state, which was recently identified as an excited state in carotenoids bound in bacterial light-harvesting complexes, exhibits a different response to the increase of excitation intensity than the S(1) state, which suggests that the models used so far to describe the excited states of carotenoids are incomplete. We propose two new models that can describe both the time-resolved and the intensity-dependent data; the first postulates that S(1) and S* are not populated in parallel after the decay of the initially excited S(2) state but instead result from the excitation of distinct ground-state subpopulations. The second model introduces a resonantly enhanced light-induced transition during excitation, which promotes population to higher-lying excited states that favors the formation of S* over S(1). Multiwavelength target analysis of the time-resolved and excitation-intensity dependence measurements were used to characterize the involved states and their responses. We show that both proposed models adequately fit the measured data, although it is not possible to determine which model is most apt. The physical origins and implications of both models are explored.     

FDTD analysis of photonic crystal defect layers filled with liquid crystals

Dielectric and metallic photonic crystals comprising nematic liquid crystal materials as defect layers or elements are investigated by the Finite Difference Time Domain (FDTD) method. Appropriate formulations of the FDTD algorithm, for the simulation of anisotropic and dispersive media as well as periodic geometries, are utilised and combined with the proper absorbing and periodic boundary conditions. The spectral properties of the presented structures are tuned by means of applying static electric fields across the defect layers, thus affecting the molecular orientation of the liquid crystal material. Numerical results show that sufficient tuning ranges are achieved, requiring low operating voltages. Moreover, high and sharp resonance peaks are observed.     

Using adaptive neuro-fuzzy inference systems for the detection of centroblasts in microscopic images of follicular lymphoma

In this paper, a complete methodology for automatic detection of centroblasts (CBs) in microscopic images acquired from tissue biopsies of follicular lymphoma is presented. In the proposed method, tissue sections are sliced at a low thickness level, around 1–1.5 \(\upmu \)m, which provides a more detailed depiction of the nuclei and other textural information. Initially, images are segmented into their basic cytological components, i.e., blood cells, nuclei and extra-cellular material, and then a novel touching-cell splitting algorithm is applied using a Gaussian mixture model and expectation–maximization algorithm. Additionally, a morphological and textural analysis of CBs is applied in order to extract various features related to their nuclei, nucleoli and cytoplasm. In the final step, a novel classification scheme is proposed based on adaptive neuro-fuzzy inference systems to classify the candidate cells. The methodology yielded promising results with an average detection rate of 90.35 %.     

Polytypism in GaAs nanowires: determination of the interplanar spacing of wurtzite GaAs by X‐ray diffraction

In GaAs nanowires grown along the cubic [111]_c direction, zinc blende and wurtzite arrangements have been observed in their stacking sequence, since the energetic barriers for nucleation are typically of similar order of magnitude. It is known that the interplanar spacing of the (111)_c Ga (or As) planes in the zinc blende polytype varies slightly from the wurtzite polytype. However, different values have been reported in the literature. Here, the ratio of the interplanar spacing of these polytypes is extracted based on X‐ray diffraction measurements for thin GaAs nanowires with a mean diameter of 18–25 nm. The measurements are performed with a nano‐focused beam which facilitates the separation of the scattering of nanowires and of parasitic growth. The interplanar spacing of the (111)_c Ga (or As) planes in the wurtzite arrangement in GaAs nanowires is observed to be 0.66% ± 0.02% larger than in the zinc blende arrangement.     

A Fuzzy Multi-criteria Outranking Approach in Support of Business Angels’ Decision-Analysis Process for the Assessment of Companies as Investment Opportunities

In this paper, a multi-criteria method is presented for the evaluation and ranking of a selected set of companies as investment opportunities in aid of the relevant decision-analysis process of business angels. The multi-criteria methodology is based on the PROMETHEE method, which is further extended to deal with fuzzy input data in order to address the data imprecision and uncertainty of the decision process. The paper concludes by suggesting a web-based system implementation of the proposed methodology, which will significantly enhance modern business angels networks.     

Pattern-recognition system,designed on GPU,for discriminating between injured normal and pathological knee cartilage

The aim was to design a pattern-recognition (PR) system for discriminating between normal and pathological knee articular cartilage of the medial femoral (MFC) and tibial condyles (MTC). The data set comprised segmented regions of interest (ROIs) from coronal and sagittal 3-T magnetic resonance images of the MFC and MTC cartilage of young patients, 28 with abnormality-free knee and 16 with pathological findings. The PR system was designed employing the probabilistic neural network classifier, textural features from the segmented ROIs and the leave-one-out evaluation method, while the PR system's precision to “unseen” data was assessed by employing the external cross-validation method. Optimal system design was accomplished on a consumer graphics processing unit (GPU) using Compute Unified Device Architecture parallel programming. PR system design on the GPU required about 3.5 min against 15 h on a CPU-based system. Highest classification accuracies for the MFC and MTC cartilages were 93.2% and 95.5%, and accuracies to “unseen” data were 89% and 86%, respectively. The proposed PR system is housed in a PC, equipped with a consumer GPU, and it may be easily retrained when new verified data are incorporated in its repository and may be of value as a second-opinion tool in a clinical environment.     

Regularity for Fully Nonlinear Elliptic Equations with Neumann Boundary Data

We obtain local C ^α, C ^1,α, and C ^2,α regularity results up to the boundary for viscosity solutions of fully nonlinear uniformly elliptic second order equations with Neumann boundary conditions.     

An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries

This paper deals with a routing problem variant which considers customers to simultaneously require delivery and pick-up services. The examined problem is referred to as the Vehicle Routing Problem with Simultaneous Pick-ups and Deliveries (VRPSPD). VRPSPD is an NP-hard combinatorial optimization problem, practical large-scale instances of which cannot be solved by exact solution methodologies within acceptable computational times. Our interest was therefore focused on metaheuristic solution approaches. In specific, we introduce an Adaptive Memory (AM) algorithmic framework which collects and combines promising solution features to generate high-quality solutions. The proposed strategy employs an innovative memory mechanism to systematically maximize the amount of routing information extracted from the AM, in order to drive the search towards diverse regions of the solution space. Our metaheuristic development was tested on numerous VRPSPD instances involving from 50 to 400 customers. It proved to be rather effective and efficient, as it produced high-quality solutions, requiring limited computational effort. Furthermore, it managed to produce several new best solutions.