A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Multicarrier modulation for narrowband PCS

Investigation of multicarrier modulation has demonstrated the feasibility of using this modulation format to deliver relatively high channel bit rates (24 kbps) to a low cost, pager-like personal communications service (PCS) terminal that enjoys long battery life (e.g., one month on a few pen-light cells). This is to be compared to the 1200 bps carried by typical current paging systems or the 6250 bps attained by the new ERMES paging system. While more complex modulation formats, such as PSK and QAM, might achieve higher bit rates in less (power, size, cost) constrained environments, amplitude keying of the component subcarriers allows simple noncoherent energy detection that is found to be robust in this short message delivery application     

Iodide mediated electrolysis of acidic coke/coal suspension

Hydrogen is among the emerging energy vectors that are being developed to replace nonrenewable hydrocarbon energy sources. The preferred method to produce hydrogen without generating greenhouse gases is the electrolysis of water using renewable energy. The reduction of energy during the water electrolysis process is a desirable goal regardless of the source of electric power. Similar to ferrous/ferric mediation, iodide can be used as a mediator in the electrolysis of an acidic suspension of coke or coal. The iodide ion is oxidized at a far lower anodic potential than the alternative oxygen evolution reaction. This reduces the cell electrolysis voltage and, consequently, reduces electricity use. The iodide consumed at the anode is continuously regenerated by chemical reaction with the coke/coal in suspension.     

Altered mRNA and Protein Expression of Monocarboxylate Transporter MCT1 in the Cerebral Cortex and Cerebellum of Prion Protein Knockout Mice

The effect of a cellular prion protein (PrP^c) deficiency on neuroenergetics was primarily analyzed via surveying the expression of genes specifically involved in lactate/pyruvate metabolism, such as monocarboxylate transporters (MCT1, MCT2, MCT4). The aim of the present study was to elucidate a potential involvement of PrP^c in the regulation of energy metabolism in different brain regions. By using quantitative real-time polymerase chain reaction (qRT-PCR), we observed a marked reduction in MCT1 mRNA expression in the cortex of symptomatic Zürich I Prnp^−/− mice, as compared to their wild-type (WT) counterparts. MCT1 downregulation in the cortex was accompanied with significantly decreased expression of the MCT1 functional interplayer, the Na⁺/K⁺ ATPase α2 subunit. Conversely, the MCT1 mRNA level was significantly raised in the cerebellum of Prnp^−/− vs. WT control group, without a substantial change in the Na⁺/K⁺ ATPase α2 subunit expression. To validate the observed mRNA findings, we confirmed the observed change in MCT1 mRNA expression level in the cortex at the protein level. MCT4, highly expressed in tissues that rely on glycolysis as an energy source, exhibited a significant reduction in the hippocampus of Prnp^−/− vs. WT mice. The present study demonstrates that a lack of PrP^c leads to altered MCT1 and MCT4 mRNA/protein expression in different brain regions of Prnp^−/− vs. WT mice. Our findings provide evidence that PrP^c might affect the monocarboxylate intercellular transport, which needs to be confirmed in further studies.     

Hardness and Fracture Toughness of SiC-Particle-Reinforced MoSi2 Composites

The indentation technique has been used to evaluate the hardness and fracture toughness of SiC-reinforced MoSi₂ composites made by hot-pressing. It is seen that the toughness increases with increasing indentation crack length (under increasing load) and a probable mechanism responsible for this behavior is described. It is also observed that there is an optimum volume fraction of SiC particles for which the maximum fracture toughness of the composite can be achieved.     

Fabrication and Microstructures of MoSi2 Reinforced–Si3N4 Matrix Composites

Details of the fabrication and microstructures of hot-pressed MoSi₂ reinforced–Si₃N₄ matrix composites were investigated as a function of MoSi₂ phase size and volume fraction, and amount of MgO densification aid. No reactions were observed between MoSi₂ and Si₃N₄ at the fabrication temperature of 1750°C. Composite microstructures varied from particle–matrix to cermet morphologies with increasing MoSi₂ phase content. The MgO densification aid was present only in the Si₃N₄ phase. An amorphous glassy phase was observed at the MoSi₂–Si₃N₄ phase boundaries, the extent of which decreased with decreased MgO level. No general microcracking was observed in the MoSi₂–Si₃N₄ composites, despite the presence of a substantial thermal expansion mismatch between the MoSi₂ and Si₃N₄ phases. The critical MoSi₂ particle diameter for microcracking was calculated to be 3 μm. MoSi₂ particles as large as 20 μm resulted in no composite microcracking; this indicated that significant stress relief occurred in these composites, probably because of plastic deformation of the MoSi₂ phase.     

Novel dielectrics from IPNs derived from castor oil based polyurethanes

Three series of interpenetrating polymer networks (IPNs) based on a polyurethane (castor oil + toluene diisocyanate) with polystyrene, poly(methyl methacrylate), and poly(n-butyl methacrylate) were synthesized and characterized. Dielectric relaxation studies of these IPNs were carried out from ?150 to 100°C in the 100 Hz to 100 kHz range. The effects of structural variables such as composition, type of vinyl monomer, as well as the effect of interaction of the phases on the dielectric properties were studied. A certain degree of phase mixing was observed to exist in all series as detected by the variation of the glass-transition temperatures of the IPNs. Maxwell–Wagner–Sillars polarization at the interface of the two phases was observed. © 1994 John Wiley & Sons, Inc.     

Healing of adult male survivors of childhood sexual abuse

1. Lamotrigine is a new antiepileptic drug, chemically unrelated to currently used antiepileptic medication. Its pharmacokinetics can be influenced by concomitant antiepileptic medication. 2. This study was performed to assess the pharmacokinetic profile of lamotrigine in three groups of children treated with different types of comedication: drugs known to induce, to inhibit or to have no clinically significant influence on drug metabolism, respectively. 3. Thirty-one children aged 6 months to 5 years were included and received a 2 mg kg-1 single oral dose. Lamotrigine plasma profiles were different between the three comedication groups. The half-lives (mean +/- s.d.) were: 7.7 +/- 1.8 h, 21.9 +/- 6.8 h, 44.7 +/- 10.2 h in the "inducer', "other' and "inhibitor' groups respectively. 4. Patients were then dosed to steady state, with the dosage adjusted on the basis of the single dose pharmacokinetics to achieve a minimum plasma concentration between 1.5 and 3 mg l-1. The mean minimum plasma concentration for the three groups was 2.54 +/- 1.28 mg l-1 at steady state. 5. Dosage of lamotrigine can be optimised with knowledge of the metabolic effects of antiepileptic comedication.     

Time Windows Based Dynamic Routing in Multi-AGV Systems

This paper presents a dynamic routing method for supervisory control of multiple automated guided vehicles (AGVs) that are traveling within a layout of a given warehouse. In dynamic routing a calculated path particularly depends on the number of currently active AGVs' missions and their priorities. In order to solve the shortest path problem dynamically, the proposed routing method uses time windows in a vector form. For each mission requested by the supervisor, predefined candidate paths are checked if they are feasible. The feasibility of a particular path is evaluated by insertion of appropriate time windows and by performing the windows overlapping tests. The use of time windows makes the algorithm apt for other scheduling and routing problems. Presented simulation results demonstrate efficiency of the proposed dynamic routing. The proposed method has been successfully implemented in the industrial environment in a form of a multiple AGV control system.     

Validation of plant part measurements using a 3D reconstruction method suitable for high-throughput seedling phenotyping

In plant phenotyping, there is a demand for high-throughput, non-destructive systems that can accurately analyse various plant traits by measuring features such as plant volume, leaf area, and stem length. Existing vision-based systems either focus on speed using 2D imaging, which is consequently inaccurate, or on accuracy using time-consuming 3D methods. In this paper, we present a computer-vision system for seedling phenotyping that combines best of both approaches by utilizing a fast three-dimensional (3D) reconstruction method. We developed image processing methods for the identification and segmentation of plant organs (stem and leaf) from the 3D plant model. Various measurements of plant features such as plant volume, leaf area, and stem length are estimated based on these plant segments. We evaluate the accuracy of our system by comparing the measurements of our methods with ground truth measurements obtained destructively by hand. The results indicate that the proposed system is very promising.