[Correlation between hepatitis B virus infection and adverse pregnancy outcomes-a systematic review and meta-analysis].

Objective: To systematically evaluate the effect of hepatitis B virus (HBV) infection on the risk of adverse pregnancy outcomes. Methods: We searched PubMed, Embase, Web of Science, and Cochrane databases. Two researchers independently screened the literature, extracted data, and evaluated the quality. Meta-analysis and cumulative meta-analysis were performed using R4.4.1 software. Fixed/random effects models were used to analyze heterogeneous and non-heterogeneous results. Heterogeneous modifiers were identified by subgroup analysis. Funnel plots and Peters' test were used to analyze potential publication bias. Results: A total of 48 studies involving 92 836 HBsAg-positive pregnant women and 7 123 292 HBsAg-negative pregnant women were included. In terms of adverse pregnancy outcomes, HBV infection was significantly correlated with the occurrence of gestational diabetes mellitus [odds ratio (OR)=1.34, 95% confidence interval (CI): 1.17-1.53] and intrahepatic cholestasis (OR=2.48, 95%CI: 1.88-3.29), with statistically significant differences. In terms of adverse neonatal outcomes, HBV infection was significantly correlated with the occurrence of neonatal asphyxia (OR=1.49, 95%CI: 1.20-1.86) and preterm birth (OR=1.22, 95%CI: 1.12-1.33), with statistically significant differences. In addition, the cumulative meta-analysis demonstrated that the risk of gestational diabetes mellitus and preterm birth both tended to be stable in pregnant women with HBV infection following 2009 and 2010, respectively. The supplementary questions answered for repeated studies had limited significance. Conclusion: Intrahepatic cholestasis, gestational diabetes mellitus, neonatal asphyxia, and preterm birth occurrence risk can be raised with HBV infection in pregnant women.

[Reliability and validity of the Chinese version of parenting sense of competence scale in mothers of preschool children].

OBJECTIVE: To test the reliability and validity of the Chinese version of parenting sense of competence scale (PSOC) in Chinese mothers of preschool children, and to explore the perception of preschool children's mothers on their own parenting skills and their comfort of being a parent in Yanqing District of Beijing. METHODS: A cross-sectional survey was conducted using a convenience sample in 1 384 preschool children's mothers in Yanqing District of Beijing. SPSS 21.0 and Mplus 7.4 software were used for statistical analysis to test the structural validity, criterion related validity, internal consistency and split half reliability of the scale, and to analyze the score of the scale and its influencing factors. RESULTS: The PSOC had good reliability and validity. Exploratory factor analysis showed that each item of the PSOC had more than 0.4 factor loading in efficacy factor or satisfaction factor, and there was no double load phenomenon. Confirmatory factor analysis showed that the factor loadings ranged from 0.212 to 0.843 in efficacy factor and satisfaction factor, respectively. The goodness of fit test showed that all the fitting indexes were within the acceptable range, and the correlation between the effectiveness subscale and the satisfaction subscale was high. The Cronbach's α coefficient of the whole scale, the efficacy subscale and the satisfaction subscale were 0.872, 0.802, and 0.874, respectively. The Spearman-Brown coefficient of PSOC was 0.851. The average score of the whole scale, the efficacy subscale, and the satisfaction subscale were 72.33±11.31, 35.54±5.91, and 36.79±7.11, respectively, and the score of parenting competence in Chinese mothers of preschool children was influenced by the mother's educational level and the annual income of her family. CONCLUSION: The PSOC has satisfactory reliability and validity in Chinese mothers of preschool children. It can be used as an evaluation instrument for measuring the parenting competency, self perceived efficacy and satisfaction in the mainland Chinese mothers of preschool children. The competency of preschool children's mothers in Yanqing District of Beijing is very good, which may be related to the higher education level of the mothers and the higher annual income of their families in this study.

[Quantitative evaluation of image quality of megavoltage computed tomography for guiding helical tomotherapy].

OBJECTIVE: To quantitatively analyze image quality of two sets of phantom (CatPhan504 and Cheese) Megavoltage computed tomography (MVCT) images acquired by Helical Tomotherapy with three scanning modes (Fine, Normal and Coarse), and to explore and validate a semi-automatic quality assurance procedure for MVCT images of Helical Tomotherapy. METHODS: On Helical Tomotherapy, CatPan504 and Cheese phantoms were scanned with three pitch levels (Fine, Normal, Coarse: 4 mm, 8 mm, 12 mm/circle) respectively. Pylinac, Matlab and Eclipse were used to calculate and compare spatial resolution, noise level and low contrast resolution of images obtained under three scanning modes respectively. The spatial resolution can be evaluated by the blurring of line-pair CT value in the images of CatPhan504's CTP528 module. The noise level can be evaluated by the integral non-uniformity in the images of Cheese's uniformity module. the low contrast resolution can be evaluated by contrast-to-noise ratio of both phantoms' plug-in module, or visibility of the region of interest (Supra-Slice) in the images of CatPhan504's CTP515 module. RESULTS: Analyses on CatPhan504's line pair module(CTP528 module) showed that the first three line pairs(the gap size are 0.500 cm, 0.250 cm and 0.167 cm respectively) could be clearly observed but blurring began to occur from the fourth line pair(the gap size is 0.125 cm) under Coarse mode. Meanwhile, the first four line pairs were all observable under the Normal and Fine modes. Integral non-integrity index(the value negatively correlated with the noise level) were 0.155 7, 0.136 8 and 0.122 9 for Coarse, Normal and Fine modes respectively. None of the Supra-Slice in CatPhan504's CTP515 module could be observed under three imaging modes. Low contrast contrast-to-noise ratio of Cheese phantom was similar under three modes and the insert visibility exhibited nearly linear growth with the increasing difference between CT average value of the insert material and background. CONCLUSION: Superiority and inferiority of three image modes in terms of the three image quality index was not consistent. Evaluation results above could provide reference for more rational decision on scanning modes selection of helical tomotherapy, which was based on image visualization demands in clinical practice. The proposed method could also provide guidance for similar image quality assessment and periodic quality assurance.

[Present treatment situation of hepatocellular carcinoma with extrahepatic metastasis].

With the development of diagnostic and screening technologies, the incidence of hepatocellular carcinoma (HCC) with extrahepatic metastasis is increasing. It is a kind of refractory disease with extremely poor prognosis. Currently, there is no standard therapy. The existing guidelines only recommend targeted therapy, systemic chemotherapy or best supportive care for HCC patients with extrahepatic metastasis, but have not mentioned surgical therapy.Several studies have shown that the majority of HCC patients with extrahepatic metastasis died of progressive intrahepatic tumor leading to hepatic failure, but not extrahepatic metastases; and primary tumor resection may have a favorable impact on the prognosis of these patients with resectable primary tumors.Furthermore, the role of resection of metastatic tumors for HCC patients with extrahepatic metastasis remains unclear so far.Majority of experts think that resection of lung metastases has survival benefit when the hepatic lesion is resected or controlled, whereas resection of lymph nodes, bone metastases, adrenal gland lesions, or brain metastases does not prolong survival, which may be recommended when the goal is to relieve symptoms or improve quality of life.Therefore, surgical treatment is important for HCC patients with extrahepatic metastasis, and surgical therapy combined with personalized systemic treatment shows survival benefit for selected patients.

[Construction and validation of an in-hospital mortality risk prediction model for patients receiving VA-ECMO: a retrospective multi-center case-control study].

OBJECTIVE: To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation (VA-ECMO). METHODS: We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January, 2015 and January, 2022 using a convenience sampling method. The patients were divided into a derivation cohort (201 cases) and a validation cohort (101 cases). Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients, based on which a risk prediction model was established in the form of a nomogram. The receiver operator characteristic (ROC) curve, calibration curve and clinical decision curve were used to evaluate the discrimination ability, calibration and clinical validity of this model. RESULTS: The in-hospital mortality risk prediction model was established based the risk factors including hypertension (OR=3.694, 95% CI: 1.582-8.621), continuous renal replacement therapy (OR=9.661, 95%CI: 4.103-22.745), elevated Na2 + level (OR=1.048, 95% CI: 1.003-1.095) and increased hemoglobin level (OR=0.987, 95% CI: 0.977-0.998). In the derivation cohort, the area under the ROC curve (AUC) of this model was 0.829 (95% CI: 0.770-0.889), greater than those of the 4 single factors (all AUC < 0.800), APACHE II Score (AUC=0.777, 95% CI: 0.714-0.840) and the SOFA Score (AUC=0.721, 95% CI: 0.647-0.796). The results of internal validation showed that the AUC of the model was 0.774 (95% CI: 0.679-0.869), and the goodness of fit test showed a good fitting of this model (χ2=4.629, P>0.05). CONCLUSION: The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation, calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system, and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

[Comparison of the application methods and effects of skin flaps in the repair of defects in different parts of the nose according to the concept of aesthetic nosesubunits].

Objective: To analyze the difference of application methods and effects of local flap in small and medium-sized defects of different aesthetic subunits of nose, in order to provide reference for clinical work. Methods: A retrospective analysis was made on 59 patients with external nasal masses and scars who underwent surgical treatment in the Department of Aesthetic Plastic Surgery of the Affiliated Hospital of Qingdao University from July 1, 2021 to January 30, 2022, including 27 females and 32 males, aged 15 to 69 years. Using Likert scale, the repair methods and effects of local flap for nasal soft tissue defects were evaluated and summarized from three aspects of texture, flatness and scar concealment. GraphPad Prism 5.0 software was used for data statistics and analysis. Results: The use of skin flaps to repair small and medium-sized areas of the nose could achieve satisfactory results. For patients with different subunits, in terms of skin flatness and scar concealment degree in the operation area, patients' satisfaction with the dorsal and lateral nasal areas was higher than that of the alar and tip areas, respectively (F=6.40, P=0.001; F=10.57, P<0.001). For patients with different skin flap repair methods, the satisfaction of patients with Z-plasty and Dufourmentel skin flap was higher than that of other skin flap repair methods (F=4.38, P=0.002), and the satisfaction of patients with Dufourmentel skin flap was the highest in the degree of scar concealment (F=2.57, P=0.038). Conclusions: In the small and medium-sized defects of the nose, the use of multiple local flaps can achieve good cosmetic effects and functional recovery. The operator should select the appropriate flap repair method according to the characteristics of different aesthetic subunits of the nose.

Estimation of broadband emissivity (8-12 um) from ASTER data by using RM-NN.

Land surface window emissivity is a key parameter for estimating the longwave radiative budget. The combined radiative transfer model (RM) with neural network (NN) algorithm is utilized to directly estimate the window (8-12 um) emissivity from the brightness temperature of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with 90 m spatial resolution. Although the estimation accuracy is very high when the broadband emissivity is estimated from AST05 (ASTER Standard Data Product) by using regression method, the accuracy of AST05 is about ± 0.015 for 86 spectra which is determined by the atmosphere correction for ASTER 1B data. The MODTRAN 4 is used to simulate the process of radiance transfer, and the broadband emissivity is directly estimated from the brightness temperature of ASTER 1B data at satellite. The comparison analysis indicates that the RM-NN is more competent to estimate broadband emissivity than other method when the brightness temperatures of band 11, 12, 13, 14 are made as input nodes of dynamic neural network. The estimation average accuracy is about 0.009, and the estimation results are not sensitive to instrument noise. The RM-NN is applied to extract broadband emissivity from an image of ASTER 1B data in China, and the comparison against a classification based multiple bands with 15 m spatial resolution shows that the estimation results from RM-NN are very good.

Mafa expression enhances glucose-responsive insulin secretion in neonatal rat beta cells.

AIM/HYPOTHESIS: Neonatal beta cells lack glucose-stimulated insulin secretion and are thus functionally immature. We hypothesised that this lack of glucose responsiveness results from a generalised low expression of genes characteristic of mature functional beta cells. Important glucose-responsive transcription factors, Mafa and Pdx1, regulate genes involved in insulin synthesis and secretion, and have been implicated in late beta cell development. The aim of this study was to assess whether Mafa and/or Pdx1 regulates the postnatal functional maturation of beta cells. METHODS: By quantitative PCR we evaluated expression of these and other beta cell genes over the first month compared with adult. After infection with adenovirus expressing MAFA, Pdx1 or green fluorescent protein (Gfp), P2 rat islets were evaluated by RT-PCR and insulin secretion with static incubation and reverse haemolytic plaque assay (RHPA). RESULTS: At P2 most beta cell genes were expressed at about 10% of adult, but by P7 Pdx1 and Neurod1 no longer differ from adult; by contrast, Mafa expression remained significantly lower than adult through P21. Overexpression of Pdx1 increased Mafa, Neurod1, glucokinase (Gck) mRNA and insulin content but failed to enhance glucose responsiveness. Similar overexpression of MAFA resulted in increased Neurod1, Nkx6-1, Gck and Glp1r mRNAs and no change in insulin content but, importantly, acquisition of glucose-responsive insulin secretion. Both the percentage of secreting beta cells and the amount of insulin secreted per beta cell increased, approaching that of adult beta cells. CONCLUSIONS/INTERPRETATION: In the process of functional maturation acquiring glucose-responsive insulin secretion, neonatal beta cells undergo a coordinated gene expression programme in which Mafa plays a crucial role.

Infestation and distribution of chigger mites on Brown rat (Rattus norvegicus) in Yunnan Province, Southwest China.

Chigger mites is a group of arthropods and some of them are vectors of scrub typhus. As a common synanthropic rodent species, the Brown rat (Rattus norvegicus) often harbors lots of ectoparasites including chigger mites. According to some "data mining" strategies, the present study took the advantage of the abundant original data from a long-term field ecological investigation between 2001 and 2015 to make a detailed analysis of chigger mites on R. norvegicus in Yunnan Province, Southwest of China. From 18 of 33 investigated counties, only 1414 chigger mites were collected from 1113 Brown rats with relatively low infestations. The 1414 individual chigger mites were identified as comprising 61 species, 11 genera and 2 subfamilies of the family Trombiculidae with a high species diversity (S=61, H'=3.13). Of 61 mite species, there were four main species, Walchia ewingi, Ascoschoengastia indica, W. koi and A. rattinorvegici, which accounted for 44.41% of the total mites. All the chigger mites were of aggregated distribution among different individuals of R. norvegicus. The Brown rats in the outdoor habitats harbored much more individuals and species of chigger mites with a higher mean abundance (MA=1.46) and mean intensity (MI=12.53) than in the indoor habitats (P<0.05). The overall infestation of the rats was significantly higher in the mountainous landscapes than in the flatland landscapes (P<0.001). The species similarity (Css) of the mites on the male and female rats reached 64.44% with sex biased infestations. The male rats harbored more species and individuals of the mites than the female rats. The adult rats harbored more species and individuals of the mites than the juvenile rats. The species abundance distribution of the mites was successfully fitted by Preston's lognormal model with s(R)=15e-[0.31(R-1)]2 (α=0.31, R2=0.95). On the basis of fitting the theoretical curve by Preston's model, the total mite species on R. norvegicus was estimated to be 86 species, and 25 rare mite species were missed in the sampling field investigation. The curve tendency of the species-plot relationship indicates that R. norvegicus have a great potential to harbor many species of chigger mites, and more species of the mites would be collected if more rats are sampled.

Estimation of water vapor content in near-infrared bands around 1 mum from MODIS data by using RM-NN.

An algorithm based on the radiance transfer model (RM) and a dynamic learning neural network (NN) for estimating water vapor content from moderate resolution imaging spectrometer (MODIS) 1B data is developed in this paper. The MODTRAN4 is used to simulate the sun-surface-sensor process with different conditions. The dynamic learning neural network is used to estimate water vapor content. Analysis of the simulation data indicates that the mean and standard deviation of estimation error are under 0.06 gcm(-2 )and 0.08 gcm(-2). The comparison analysis indicates that the estimation result by RM-NN is comparable to that of a MODIS water vapor content product (MYD05_L2). Finally, validation with ground measurement data shows that RM-NN can be used to accurately estimate the water vapor content from MODIS 1B data, and the mean and standard deviation of the estimation error are about 0.12 gcm(-2 )and 0.18 gcm(-2).

A possible role of chorion protease in shell membrane degradation during development of quail embryos.

In the eggs of the quail Coturnix japonica, the limiting membrane demarcates the shell membrane at the interface with the albumen and decreases in width during the hatching process. This study was done to identify agents that affect the width of this limiting membrane. Zymography tests on extracts from extraembryonic tissues, yolk sacs, or chorioallantoic membranes, or all three, showed proteolytic activities during d 4 to 10 of incubation. Localization experiments on these activities, performed on d 5 eggs, indicated that they were located in an avascular chorion. Electron microscopic analysis showed there were secretory cells specifically located in the avascular chorion. After partial purification of d 5 avascular chorion extracts using QA52 and Sephadex G-200 column chromatography, the proteolytic activity of 20 kDa was isolated. The protease showed a high level of activity toward succinyl-Gly-Pro-Leu-Gly-Pro-4-methylcoumaryl-7-amide. It had an optimal pH of 9 and digested the limiting membrane. These enzymatic activities were inhibited moderately by EDTA and strongly by leupeptin and aprotinin. It was concluded that it is the 20-kDa protease, showing collagenase-like activity produced by the avascular chorion, that affects the limiting membrane.

Lactobacillus acidophilus and Clostridium butyricum ameliorate colitis in murine by strengthening the gut barrier function and decreasing inflammatory factors.

Ulcerative colitis is a type of chronic inflammation present in the intestines for which the aetiology is not yet clear. The current therapies for ulcerative colitis cannot be considered to be long-term management strategies due to their significant side effects. Therefore, it is essential to identify an alternative therapeutic strategy for ulcerative colitis. The present study focused on the evaluation of the anti-inflammatory activities of Lactobacillus acidophilus CGMCC 7282 and Clostridium butyricum CGMCC 7281. The roles of both single and combination of L. acidophilus CGMCC 7282 and C. butyricum CGMCC 7281 in ulcerative colitis were investigated in 2,4,6-trinitrobenzenesulfonic acid-induced acute colitis (Th1-type colitis) in Sprague-Dawley rats and oxazolone-induced chronic colitis (Th2-type colitis) in BALB/c mice. The in vivo studies showed that the administration of L. acidophilus CGMCC 7282, C. butyricum CGMCC 7281 and L. acidophilus CGMCC 7282 plus C. butyricum CGMCC 7281 could reduce the Th1-type colitis as well as the Th2-type colitis, and the combination of the two strains exhibited the most notable effects, as indicated by the reduced mortality rates, the suppressed disease activity indices, the improved body weights, the reduced colon weight/colon length and colon weight/body weight ratios, and the improved gross anatomic characteristics and histological features (ameliorations of neutrophil infiltration and ulceration in the colon). It was found that the alterations of the gut microbiome, the barrier function changing and the selected inflammation-related cytokines are observed in the ulcerative colitis rats/mice treated with L. acidophilus CGMCC 7282 and C. butyricum CGMCC 7281. The combination of L. acidophilus CGMCC 7282 plus C. butyricum CGMCC 7281 also exerted a stronger anti-inflammatory effect than either of the single strains alone in vitro. These findings provide evidence that the administration of L. acidophilus CGMCC 7282 plus C. butyricum CGMCC 7281 may be a promising therapy for ulcerative colitis.

The ties problem resulting from counting-based error estimators and its impact on gene selection algorithms.

MOTIVATION: Feature selection approaches, such as filter and wrapper, have been applied to address the gene selection problem in the literature of microarray data analysis. In wrapper methods, the classification error is usually used as the evaluation criterion of feature subsets. Due to the nature of high dimensionality and small sample size of microarray data, however, counting-based error estimation may not necessarily be an ideal criterion for gene selection problem. RESULTS: Our study reveals that evaluating genes in terms of counting-based error estimators such as resubstitution error, leave-one-out error, cross-validation error and bootstrap error may encounter severe ties problem, i.e. two or more gene subsets score equally, and this in turn results in uncertainty in gene selection. Our analysis finds that the ties problem is caused by the discrete nature of counting-based error estimators and could be avoided by using continuous evaluation criteria instead. Experiment results show that continuous evaluation criteria such as generalised the absolute value of w2 measure for support vector machines and modified Relief's measure for k-nearest neighbors produce improved gene selection compared with counting-based error estimators. AVAILABILITY: The companion website is at http://www.ntu.edu.sg/home5/pg02776030/wrappers/ The website contains (1) the source code of all the gene selection algorithms and (2) the complete set of tables and figures of experiments.

TIMP-1 mediates the inhibitory effect of interleukin-6 on the proliferation of a hepatocarcinoma cell line in a STAT3-dependent manner.

The tissue inhibitor of metalloproteinases (TIMP)-1 is a multifunctional protein which is not only an inhibitor of matrix metalloproteinases (MMPs) but also to have a possible "cytokine-like" action. Here, we first compared mRNA expression of TIMP-1 and MMP-9 in BEL-7402 (a hepatocellular carcinoma cell line), L-02 (a normal liver cell line) and QSG-7701 (a cell line derived from peripheral tissue of liver carcinoma) using real-time quantitative RT-PCR. By evaluating the variation of the MMP-9/TIMP-1 ratio as an index of reciprocal changes of the expression of the two genes, we observed that the MMP-9/TIMP-1 ratio was about 13- and 5-fold higher in BEL-7402 than in L-02 and QSG-7701, respectively. Significantly, overexpression of TIMP-1 decreased the MMP-9/TIMP-1 ratio in BEL-7402 and then inhibited the cell growth to 60% and reduced the migration to about 30%. Meanwhile, our data showed that interleukin-6 (IL-6) (100 ng/mL) could also inhibited the cell growth of BEL-7402. Further studies indicated that TIMP-1 mediated the inhibitory effect of IL-6 on BEL-7402 cell proliferation in a STAT3-dependent manner, which could further accelerate the expression of the cyclin-dependent kinase inhibitor p21. A dominant negative STAT3 mutant totally abolished IL-6-induced TIMP-1 expression and its biological functions. The present results demonstrate that TIMP-1 may be one of the mediators that regulate the inhibitory effect of IL-6 on BEL-7402 proliferation in which STAT3 signal transduction and p21 up-regulation also play important roles.

Supervised learning-based cell image segmentation for p53 immunohistochemistry.

In this paper, we present two new algorithms for cell image segmentation. First, we demonstrate that pixel classification-based color image segmentation in color space is equivalent to performing segmentation on grayscale image through thresholding. Based on this result, we develop a supervised learning-based two-step procedure for color cell image segmentation, where color image is first mapped to grayscale via a transform learned through supervised learning, thresholding is then performed on the grayscale image to segment objects out of background. Experimental results show that the supervised learning-based two-step procedure achieved a boundary disagreement (mean absolute distance) of 0.85 while the disagreement produced by the pixel classification-based color image segmentation method is 3.59. Second, we develop a new marker detection algorithm for watershed-based separation of overlapping or touching cells. The merit of the new algorithm is that it employs both photometric and shape information and combines the two naturally in the framework of pattern classification to provide more reliable markers. Extensive experiments show that the new marker detection algorithm achieved 0.4% and 0.2% over-segmentation and under-segmentation, respectively, while reconstruction-based method produced 4.4% and 1.1% over-segmentation and under-segmentation, respectively.

Regularization network-based gene selection for microarray data analysis.

Microarray data contains a large number of genes (usually more than 1000) and a relatively small number of samples (usually fewer than 100). This presents problems to discriminant analysis of microarray data. One way to alleviate the problem is to reduce dimensionality of data by selecting important genes to the discriminant problem. Gene selection can be cast as a feature selection problem in the context of pattern classification. Feature selection approaches are broadly grouped into filter methods and wrapper methods. The wrapper method outperforms the filter method but at the cost of more intensive computation. In the present study, we proposed a wrapper-like gene selection algorithm based on the Regularization Network. Compared with classical wrapper method, the computational costs in our gene selection algorithm is significantly reduced, because the evaluation criterion we proposed does not demand repeated training in the leave-one-out procedure.

Neuron selection for RBF neural network classifier based on data structure preserving criterion.

The central problem in training a radial basis function neural network is the selection of hidden layer neurons. In this paper, we propose to select hidden layer neurons based on data structure preserving criterion. Data structure denotes relative location of samples in the high-dimensional space. By preserving the data structure of samples including those that are close to separation boundaries between different classes, the neuron subset selected retains the separation margin underlying the full set of hidden layer neurons. As a direct result, the network obtained tends to generalize well.

Fast modular network implementation for support vector machines.

Support vector machines (SVMs) have been extensively used. However, it is known that SVMs face difficulty in solving large complex problems due to the intensive computation involved in their training algorithms, which are at least quadratic with respect to the number of training examples. This paper proposes a new, simple, and efficient network architecture which consists of several SVMs each trained on a small subregion of the whole data sampling space and the same number of simple neural quantizer modules which inhibit the outputs of all the remote SVMs and only allow a single local SVM to fire (produce actual output) at any time. In principle, this region-computing based modular network method can significantly reduce the learning time of SVM algorithms without sacrificing much generalization performance. The experiments on a few real large complex benchmark problems demonstrate that our method can be significantly faster than single SVMs without losing much generalization performance.

Identifying critical variables of principal components for unsupervised feature selection.

Principal components analysis (PCA) is probably the best-known approach to unsupervised dimensionality reduction. However, axes of the lower-dimensional space, ie., principal components (PCs), are a set of new variables carrying no clear physical meanings. Thus, interpretation of results obtained in the lower-dimensional PCA space and data acquisition for test samples still involve all of the original measurements. To deal with this problem, we develop two algorithms to link the physically meaningless PCs back to a subset of original measurements. The main idea of the algorithms is to evaluate and select feature subsets based on their capacities to reproduce sample projections on principal axes. The strength of the new algorithms is that the computaion complexity involved is significantly reduced, compared with the data structural similarity-based feature evaluation.

Penetration depth scaling for impact into wet granular packings.

We present experimental measurements of penetration depths for the impact of spheres into wetted granular media. We observe that the penetration depth in the liquid saturated case scales with projectile density, size, and drop height in a fashion consistent with the scaling observed in the dry case, but with smaller penetrations. Neither viscous drag nor density effects can explain the enhancement to the stopping force. The penetration depth exhibits a complicated dependence on liquid fraction, accompanied by a change in the drop-height dependence, that must be the consequence of accompanying changes in the conformation of the liquid phase in the interstices.