Neurons and fractals: how reliable and useful are calculations of fractal dimensions?

alpha-Amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors are critically involved in several forms of synaptic plasticity proposed to be neural substrates for learning and memory, e.g., long-term potentiation and long-term depression (LTD). The present study was designed to determine changes in cerebellar AMPA receptors following classical conditioning of the eyeblink-nictitating membrane response (NMR) in the rabbit. Quantitative autoradiography was used to assess changes in ligand binding properties of cerebellar AMPA receptors following NMR conditioning elicited by pairing electrical stimulation of the pontine nuclei with an airpuff to the eye. [3H]AMPA and [3H]-6-cyano-7-nitroquinoxaline-2,3-dion (CNQX) binding were determined following preincubation of frozen-thawed brain tissue sections at 0 or 35 degreesC. With 0 degreesC preincubation, no significant differences in [3H]AMPA binding to cerebellar AMPA receptors were seen between any of the experimental groups tested. In contrast, preincubation at 35 degreesC revealed significant decreases in [3H]AMPA binding to the trained side of the cerebellar cortex resulting from paired presentations of the conditioned and the unconditioned stimuli, while unpaired presentations of the stimuli resulted in no significant effect. With 35 degreesC preincubation, there were no significant differences in [3H]CNQX binding between any of the experimental groups and no significant differences in [3H]AMPA binding in the untrained side of the cerebellum. These results indicate that NMR conditioning is associated with a selective modification of AMPA-receptor properties in brain structures involved in the storage of the associative memory. Furthermore, they support the hypothesis that cerebellar LTD, resulting from decreased synaptic efficacy at parallel fiber-Purkinje cell synapses mediated by a change in AMPA-receptor properties, is a form of synaptic plasticity that supports this type of learning.     

一种模糊控制小生境遗传算法的应用研究

基于遗传算法的基本原理,提出一种改进的遗传算法,将模糊控制思想与小生境技术引入到其中,从而保护种群的多样性,同时使每代最优解得以保存．遗传算法加入小生境技术后虽可保持种群群体的多样性,但是不可避免的会产生部分个体的早熟以及陷入局部最优,于是加入模糊控制思想,对种群的交叉概率P_c和变异概率P_m进行模糊控制,以此为基础,形成了一种新型的模糊控制小生境遗传算法．最后通过对三个典型函数的数值分析证明了该方法的有效性和可行性．     

Edge detection in medical images using a genetic algorithm

An algorithm is developed that detects well-localized, unfragmented, thin edges in medical images based on optimization of edge configurations using a genetic algorithm (GA). Several enhancements were added to improve the performance of the algorithm over a traditional GA. The edge map is split into connected subregions to reduce the solution space and simplify the problem. The edge-map is then optimized in parallel using incorporated genetic operators that perform transforms on edge structures. Adaptation is used to control operator probabilities based on their participation. The GA was compared to the simulated annealing (SA) approach using ideal and actual medical images from different modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound. Quantitative comparisons were provided based on the Pratt figure of merit and on the cost-function minimization. The detected edges were thin, continuous, and well localized. Most of the basic edge features were detected. Results for different medical image modalities are promising and encourage further investigation to improve the accuracy and experiment with different cost functions and genetic operators.     

Heredity and systemic lupus erythematosus: dissecting a complex genetic disease

The etiology of SLE appears to be exceedingly complex and possibly heterogeneous, with genetics and environment both making substantial contributions. A schematic representation of potential mechanisms is depicted in Figure 2. We may not fully understand the pathogenesis of this disease until we unravel the relative contributions of each component to the development of SLE. While genetic mechanisms involved in SLE remain obscure, we now have available elegant laboratory techniques for analysis of genetic loci as well as computer technology which permits simulation and analysis of the transmission of complex genetic traits among multiple families and demographic groups. What remains is the painstaking task of collecting families multiplex for SLE and analyzing multiple sets of clinical, serologic, and genetic data within and between these pedigrees. Such studies are currently underway and will hopefully increase understanding of this enigmatic and complex autoimmune disorder.     

An algorithm for modelling microstructural development in weld heat-affected zones (part a) reaction kinetics

A computer algorithm originally developed for predicting the hardenability of low alloy steels has been adapted to forecast the microstructural development in weld heat-affected zones (HAZ). This algorithm simulates the kinetics of the decomposition of austenite to its various daughter products. When combined with a suitable model of the heat transfer in weld HAZ's, it provides a useful tool to predict the resultant microstructure. Thus, it allows one to optimize welding process parameters to achieve the best microstructure possible.     

Digital simulations of a stationary and a linear weld

A computational model was used to simulate stationary and linear gas-tungsten-arc (GTA) welds and to study the effect of surface-tension as well as arc position. The results show that the surface-tension gradient with respect to temperature is a dominating factor in determining the direction of the convective flow within the molten weld pool. Furthermore, a linear-arc movement leads to a convective pattern, which is different from that of a stationary weld.     

混合流水车间调度模型及其遗传算法

针对流程工业生产过程连续性的特点,从一种新的角度建立了工件等待时间受限的混合流水车间调度模型.以总完工时间最小化和工件在各机器最早开工时间最小化为目标函数,利用改进的遗传算法生成最优排序计划,并用模拟的实际生产数据对模型和算法进行验证和分析.     

Prediction of hemorrhagic blood loss with a genetic algorithm neural network

There is no established method for accurately predicting how much blood loss has occurred during hemorrhage. In the present study, we examine whether a genetic algorithm neural network (GANN) can predict volume of hemorrhage in an experimental model in rats and we compare its accuracy to stepwise linear regression (SLR). Serial measurements of heart period; diastolic, systolic, and mean blood pressures; hemoglobin; pH; arterial PO2; arterial PCO2; bicarbonate; base deficit; and blood loss as percent of total estimated blood volume were made in 33 male Wistar rats during a stepwise hemorrhage. The GANN and SLR used a randomly assigned training set to predict actual volume of hemorrhage in a test set. Diastolic blood pressure, arterial PO2, and base deficit were selected by the GANN as the optimal predictors set. Root mean square error in prediction of estimated blood volume by GANN was significantly lower than by SLR (2.63%, SD 1.44, and 4.22%, SD 3.48, respectively; P < 0.001). A GANN can predict highly accurately and significantly better than SLR volume of hemorrhage without knowledge of prehemorrhage status, rate of blood loss, or trend in physiological variables.     

混合遗传算法对混流装配线平衡问题的研究

基于面向汽车行业总装生产线平衡问题的研究,提出了一种包含模拟退火因子的改进的遗传算法,设计了加速收敛因子模型以确保在有限种群空间中的快速收敛;同时考虑了更多工程现场实际约束来修正传统的约束模型.新算法模型应用在混流装配生产线平衡分析中,取得了算法快速收敛和分析结果与实际工程一致的结果.     

神经网络与遗传算法预测充填配比的研究

为确定最优充填配比方案,在实验的基础上,基于神经网络遗传算法,预测全局最优充填实验条件,最优实验条件为灰砂质量比0.2024,养护时间5.863 d,溶度67.8%,最大充填体抗压强度0.6777 MPa,与实际最佳配比方案灰砂质量比1∶4、养护天数28 d、溶度75%、最大抗压强度5.48 MPa相差较大,预测结果不是很满意.说明该方法有较强的适用条件,神经网络的预测精度对遗传算法的极值寻优有影响,建议扩大样本的数量.     

基于遗传算法的可重入钢管生产优化调度

在可重入冷拔无缝钢管生产的计划和调度中,根据四个条件对工件进行组批,通过规则假设把组批后的批钢管看作单个加工工件,建立以最后完工时间、交货期满意度和机器总负荷为目标的多目标组批排序优化模型,设定其约束条件,采用基于Pareto的混合遗传算法对模型进行优化求解.通过算例证明该模型的有效性和合理性.     

Cord formation in BACTEC medium is a reliable, rapid method for presumptive identification of Mycobacterium tuberculosis complex

Serpentine cord formation in BACTEC 12B medium was evaluated as a rapid method for the presumptive identification of M. tuberculosis complex. Kinyoun acid-fast stained smears were prepared from 666 positive BACTEC 12B bottles and examined for the presence or absence of serpentine cording. Cord formation had a sensitivity, specificity, positive predictive value, and negative predictive value of 89.2, 99.2, 98.5, and 94.2%, respectively. The evaluation of the presence of cord formation in BACTEC 12B medium is reliable and permits the rapid presumptive reporting of M. tuberculosis.     

Distortion of Palmaz-Schatz stent geometry following side-branch balloon dilation through the stent in a rabbit model

In this prospective study, we have compared women undergoing laparoscopic cholecystectomy, laparoscopic gynaecological surgery and laparoscopic minor gynaecological procedures (diagnostic, tubal, ligation) (n = 10 in each group) to determine if lower abdominal laparoscopy results in less postoperative pulmonary dysfunction than upper abdominal laparoscopy. Pulmonary testing was performed before operation, and 3 and 6 h after operation, on the first and second days after surgery. After operation, a significant reduction in forced vital capacity, forced expiratory volume in 1 s and peak expiratory flow rate occurred after laparoscopic cholecystectomy at each time. There were no significant changes after minor gynaecologic laparoscopy, whereas laparoscopic gynaecological surgery resulted in minor pulmonary dysfunction on the day of surgery only. We conclude that postoperative pulmonary function was less impaired after gynaecological laparoscopy than after laparoscopic cholecystectomy. This study suggests that the site of surgery is an important determinant of lung dysfunction after laparoscopy.     

Design of a high-sensitivity classifier based on a genetic algorithm: application to computer-aided diagnosis

A genetic algorithm (GA) based feature selection method was developed for the design of high-sensitivity classifiers, which were tailored to yield high sensitivity with high specificity. The fitness function of the GA was based on the receiver operating characteristic (ROC) partial area index, which is defined as the average specificity above a given sensitivity threshold. The designed GA evolved towards the selection of feature combinations which yielded high specificity in the high-sensitivity region of the ROC curve, regardless of the performance at low sensitivity. This is a desirable quality of a classifier used for breast lesion characterization, since the focus in breast lesion characterization is to diagnose correctly as many benign lesions as possible without missing malignancies. The high-sensitivity classifier, formulated as the Fisher's linear discriminant using GA-selected feature variables, was employed to classify 255 biopsy-proven mammographic masses as malignant or benign. The mammograms were digitized at a pixel size of 0.1 mm x 0.1 mm, and regions of interest (ROIs) containing the biopsied masses were extracted by an experienced radiologist. A recently developed image transformation technique, referred to as the rubber-band straightening transform, was applied to the ROIs. Texture features extracted from the spatial grey-level dependence and run-length statistics matrices of the transformed ROIs were used to distinguish malignant and benign masses. The classification accuracy of the high-sensitivity classifier was compared with that of linear discriminant analysis with stepwise feature selection (LDAsfs). With proper GA training, the ROC partial area of the high-sensitivity classifier above a true-positive fraction of 0.95 was significantly larger than that of LDAsfs, although the latter provided a higher total area (Az) under the ROC curve. By setting an appropriate decision threshold, the high-sensitivity classifier and LDAsfs correctly identified 61% and 34% of the benign masses respectively without missing any malignant masses. Our results show that the choice of the feature selection technique is important in computer-aided diagnosis, and that the GA may be a useful tool for designing classifiers for lesion characterization.     

Using a genetic algorithm to identify common structural features in sets of ligands

This article describes a program for pharmacophore mapping, called MPHIL (Mapping Pharmacophores in Ligands). Given as input a set of molecules that exhibit some common biological activity, MPHIL identifies the smallest 3D pattern of pharmacophore points that has at least m (a user-defined parameter) points in common with each of the input molecules. The program thus differs from existing programs for pharmacophore mapping in that it does not require all of the molecules to share exactly the same pattern of points, although it will find such a common pattern if it does, indeed, exist. MPHIL uses a genetic algorithm (GA) approach in which an initial, and very rapid, GA is used to suggest possible combinations of points that are then processed by the second GA to yield the final 3D pattern.