Correlating the 3D melt electrospun polycaprolactone fiber diameter and process parameters using neural networks

In the present work, we developed an artificial neural networks (ANN) model to predict and analyze the polycaprolactone fiber diameter as a function of 3D melt electrospinning process parameters. A total of 35 datasets having various combinations of electrospinning writing process variables (collector speed, tip to nozzle distance, applied pressure, and voltage) and resultant fiber diameter were considered for model development. The designed stand-alone ANN software extracts relationships between the process variables and fiber diameter in a 3D melt electrospinning system. The developed model could predict the fiber diameter with reasonable accuracy for both train (28) and test (7) datasets. The relative index of importance revealed the significance of process variables on the fiber diameter. Virtual melt spinning system with the mean values of the process variables identifies the quantitative relationship between the fiber diameter and process variables.     

NK cells can recognize different forms of class I MHC

NK recognition and lysis of targets are mediated by activation receptor(s) whose effects may be over-ridden by inhibitory receptors recognizing class I MHC on the target. Incubation of normal lymphoblasts with a peptide that can bind to their class I MHC renders them sensitive to lysis by syngeneic NK cells. By binding to class I MHC, the peptide alters or masks the target structure recognized by an inhibitory NK receptor(s). This target structure is most likely an "empty" dimer of class I heavy chain and beta2m as opposed to a "full" class I trimer formed by binding of specific peptide that is recognized by CTL.     

Regional forecasts of photovoltaic power generation according to different data availability scenarios: a study of four methods

The development of methods to forecast photovoltaic (PV) power generation regionally is of utmost importance to support the spread of such power systems in current power grids. The objective of this study is to propose and to evaluate methods to forecast regional PV power 1 day ahead of time and to compare their performances. Four forecast methods were regarded, of which two are new ones proposed in this study. Together, they characterize a set of forecast methods that can be applied in different scenarios regarding availability of data and infrastructure to make the forecasts. The forecast methods were based on the use of support vector regression and weather prediction data. Evaluations were performed for 1 year of hourly forecasts using data of 273 PV systems installed in two adjacent regions in Japan, Kanto, and Chubu. The results show the importance of selecting the proper forecast method regarding the region characteristics. For Chubu, the region with a variety of weather conditions, the forecast methods based on single systems' forecasts and the one based on stratified sampling provided the best results. In this case, the best annual normalized root mean square error (RMSE) and mean absolute error (MAE) were 0.25 and 0.15 kWh/kWh_avg, respectively. For Kanto, with homogeneous weather conditions, the four methods performed similarly. In this case, the lowest annual forecast errors were 0.33 kWh/kWh_avg for the normalized RMSE and 0.202 kWh/kWh_avg for the normalized MAE. Copyright © 2014 John Wiley & Sons, Ltd.     

Intrinsic properties of the optical coupling between axisymmetric Gaussian beams

On the basis of the overlap integral method, an approximate analytical model is derived to estimate the coupled optical power between axisymmetric Gaussian beams when transverse, axial, and angular misalignments simultaneously exist in three dimensions. Seven optical properties are derived from a detailed analysis of the model. Because the model is an approximate analytical solution to the overlap integral method, the existence of each property is also investigated by a numerical solution. Results show that all seven properties are intrinsic to the optical coupling phenomenon between Gaussian beams. Because numerous single-mode device-to-fiber coupling systems can be well described by use of Gaussian beams, the seven properties provide a solid basis to develop model-based algorithms for single-mode device-to-fiber alignment automation.     

A dynamical model for generating synthetic electrocardiogram signals

A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle, and the power spectrum of the RR tachogram. In particular, both respiratory sinus arrhythmia at the high frequencies (HFs) and Mayer waves at the low frequencies (LFs) together with the LF/HF ratio are incorporated in the model. Much of the beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation are shown to result. This model may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.     

Development, microevolution, and social behavior.

The central questions of social development—from the roots of mother–infant attachment to the plasticity of aggressive behavior—pivot on the relations between genetic and ontogenetic sources of variance. It is proposed that (a) developmental, experiential, and microevolutionary processes typically collaborate, rather than compete, in achieving social adaptation; (b) social behavior patterns are mostly closed to modification in the course of development and across generations, but avenues of vulnerability exist in ontogeny and microevolution for dynamic, rapid, and reversible changes in key features; (c) a general avenue for change is delay or acceleration in the developmental onset of one or more features of the behavior pattern, which in turn modifies the functions and properties of the adaptive configuration; and (d) the features of social behavior that are open to rapid change in ontogeny should be open as well to rapid changes in microevolution, although different underlying processes may be involved. Empirical findings from the investigation of aggressive interactions are used to illustrate this proposal on the dual genesis and coincident adaptation of social behaviors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Detection of Ectopic Beats in the Electrocardiogram Using an Auto-Associative Neural Network

Abnormal rhythms of the heart are often preceded by the occurrence of ectopic beats. These are difficult to detect as their shape is not very different from that of a normal QRS complex, the main feature in the electrocardiogram. We show how an auto-asociative multi-layer perceptron can be trained to detect normal beats only, so that the subtle abnormalities in shape of ectopic beats become clearly identifiable. This is a generic detector of abnormal beats (i.e. beats whose morphology is different from that of a normal beat) and we use ventricular ectopic beats to illustrate the performance of the algorithm. We also propose a new parameter, the variance ratio, to monitor the progress of learning in an auto-associative network.     

Influence of dry and wet cleaning on the properties of rapid thermal grown and deposited gate dielectrics

Various silicon surface cleaning processes for rapid thermal in-situ polysilicon/ oxide/silicon stacked gate structures have been evaluated. Metal-oxide-semiconductor capacitors were fabricated to assess the effects of cleaning on the quality of gate oxide structures produced by both rapid thermal oxidation (RTO) and rapid thermal chemical vapor deposition (RTCVD). Excellent electrical properties have been achieved for both RTO and RTCVD gate oxides formed on silicon wafers using either an ultraviole/zone (UV/O₃) treatment or a modified RCA clean. On the contrary, poor electrical properties have been observed for RTO and RTCVD gate oxides formed on silicon wafers using a high temperature bake in Ar, H₂, or high vacuum ambient. It has also been found that the electrical properties of the RTCVD gate oxides exhibit less dependence upon cleaning conditions than those of RTO gate oxides. This work demonstrates that initial surface condition prior to gate oxide formation plays an important role in determining the quality of RTO and RTCVD gate oxides.     

Social networks and aggressive behavior: Peer support or peer rejection?

Studied social networks and aggressive behavior in school in 2 cohorts of boys and girls in the 4th and 7th grades (N?=?695). Measures of social networks yielded convergent findings. Highly aggressive subjects (both boys and girls) did not differ from matched control subjects in terms of social cluster membership or in being isolated or rejected within the social network. Peer cluster analysis and reciprocal "best friend" selections indicated that aggressive subjects tended to affiliate with aggressive peers. Even though highly aggressive children and adolescents were less popular than control subjects in the social network at large, they were equally often identified as being nuclear members of social clusters. Aggressive subjects did not differ from matched control subjects in the number of times they were named by peers as "best friend," nor did the two groups differ in the probability of having friendship choices reciprocated by peers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)