Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature extraction for classification method using principal component based on conformal geometric algebra

This paper discusses feature extraction methods. The feature extraction methods such principal component analysis and multiple discriminant analysis are very important techniques in machine learning research areas. The characteristic of feature extraction is to transform the data from a difficultly classified space to a easily classified space. There are many conventional machine learning methods including transformation such as artificial neural network and support vector machines. However, extracting the good features before applying machine learning methods will lead to better classification results. This paper focuses on the principal component regression (PCR). The PCR finds the approximation with hyper-planes where the data distributed on. The problem now is that it has a case of the data do not distribute on hyper-planes, for example they distribute on hyper-spheres such as rotation objects, the PCR can not extract the good feature to apply the classification problems. This paper proposes a new feature extraction method by calculating the conformal eigenvectors in conformal geometric algebra(CGA) space to find the approximation hyper-planes or hyper-spheres which fit to the set of data using the least square approach. In particular, this paper shows that the classification accuracy of proposed method is better than that of conventional PCR method.
CD30 Signals the Gut Lamina Propria Requires OX40 and T Cells within + The Survival of Memory CD4

Although CD4 (cid:1) memory T cells reside within secondary lymphoid tissue, the major reservoir of these cells is in the lamina propria of the intestine. In this study, we demonstrate that, in the absence of signals through both OX40 and CD30, CD4 (cid:1) T cells are comprehensively depleted from the lamina propria. Deﬁciency in either CD30 or OX40 alone reduced CD4 (cid:1) T cell numbers, however, in mice deﬁcient in both OX40 and CD30, CD4 (cid:1) T cell loss was greatly exacerbated. This loss of CD4 (cid:1) T cells was not due to a homing defect because CD30 (cid:2) OX40-deﬁcient OTII cells were not impaired in their ability to express CCR9 and (cid:3) 4 (cid:4) 7 or trafﬁc to the small intestine. There was also no difference in the priming of wild-type (WT) and CD30 (cid:2) OX40-deﬁcient OTII cells in the mesenteric lymph node after oral immunization. However, following oral immunization, CD30 (cid:2) OX40-deﬁcient OTII cells trafﬁcked to the lamina propria but failed to persist compared with WT OTII cells. This was not due to reduced levels of Bcl-2 or Bcl-XL, because expression of these was comparable between WT and double knockout OTII cells. Collectively, these data demonstrate that signals through CD30 and OX40 are required for the survival of CD4 (cid:1) T cells within the small intestine lamina propria. The Journal of Immunology, 2009, 183: 5079–5084.
Experimental and numerical assessment of MRI‐induced temperature change and SAR distributions in phantoms and in vivo

It is important to accurately characterize the heating of tissues due to the radiofrequency energy applied during MRI. This has led to an increase in the use of numerical methods to predict specific energy absorption rate distributions for safety assurance in MRI. To ensure these methods are accurate for actual MRI coils, however, it is necessary to compare to experimental results. Here, we report results of some recent efforts to experimentally map temperature change and specific energy absorption rate in a phantom and in vivo where the only source of heat is the radiofrequency fields produced by the imaging coil. Results in a phantom match numerical simulation well, and preliminary results in vivo show measurable temperature increase. With further development, similar methods may be useful for verifying numerical methods for predicting specific energy absorption rate distributions and in some cases for directly measuring temperature changes and specific energy absorption rate induced by the radiofrequency fields in MRI experiments. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Direct and Indirect Robust Adaptive Fuzzy Controllers for a Class of Nonlinear Systems

In this paper, we propose direct and indirect adaptive fuzzy sliding mode control approaches for a class of nonaffine nonlinear systems. In the direct case, we use the implicit function theory to prove the existence of an ideal implicit feedback linearization controller, and hence approximate it to attain the desired performances. In the indirect case, we exploit the linear structure of a Takagi-Sugeno fuzzy system with constant conclusion to establish an affine-in-control model, and therefore design an indirect adaptive fuzzy controller. In both cases, the adaptation laws of the adjustable parameters are deduced from the stability analysis, in the sense of Lyapunov, to get a more accurate approximation level. In addition to their robustness, the design of the proposed approaches does not require the upper bounds of both external disturbances and approximation errors. To show the efficiency of the proposed controllers, a simulation example is presented.
Relating Knowledge Management to Business Strategy by means of an Activity Theory Framework

Knowledge Management is an emerging term currently used in organisations which recognise the need to make more effective use of their human and IT resources. The relationship, between the strategic direction of a business and its strategic approach to knowledge management, assumes that there exists collective organisational knowledge that can be managed to encourage the realisation of business goals. Knowledge in organisations can reside at four levels: the individual, the group, the organisation and the inter-organisational domain (McAdam & McCreedy 1999). While it is important to consider knowledge residing at all four levels, in this paper the emphasis will be at the organisational level. The strategic approach to organisational knowledge management will no doubt include the management of knowledge at the levels of individuals and groups within the organisation, as well as knowledge, which crossed the organisational boundary from customers, suppliers and competitors. However, as business strategy is usual driven from the senior organisational executive, this paper will focus on knowledge from a strategic organisational perspective.
Novel web page classification techniques in contextual advertising

Contextual advertising seeks to place relevant ads to generic web pages based on their contents. Recently, it has been observed that classifying web pages into a well-organized taxonomy of topics is promising for matching topically relevant ads to web pages. Following the observation, in this paper we propose two methods to increase classification accuracy for web pages in the context of contextual advertising. Our strategy is to enhance the baseline classifier by reflecting unique features of web pages and the taxonomy. In particular, category tags extracted from web pages are utilized to augment term weights, and the hierarchical structure of the taxonomy is taken into account to categorize web pages with high confidence. We conduct a series of experiments to evaluate the proposed methods, and the results show that classification accuracy is increased up to 11% compared to the baseline classifier.
Joint Power Control and Beamforming Codebook Design for MISO Channels with Limited Feedback

This paper investigates the joint design and optimization of the power control and beamforming codebooks for the single-user multiple-input single-output (MISO) wireless systems with a rate-limited feedback link. The problem is cast in the form of minimizing the outage probability subject to the transmit power constraint and cardinality constraints on the beamforming and power codebooks. We show that by appropriately choosing and fixing the beamforming codebook and optimizing the power codebook for that beamforming codebook, it is possible to achieve a performance very close to the optimal joint optimization. Further, this paper investigates the optimal tradeoffs between beamforming and power codebook sizes for different number of feedback bits and transmit antennas. Given a target outage probability, our results provide the optimal codebook sizes independent of the target rate. As the outage probability decreases, we show that the optimal joint design should use fewer feedback bits for beamforming and more feedback bits for power control. The jointly optimized beamforming and power control modules combine the power gain of beamforming and diversity gain of power control, which enable it to approach the performance of the system with perfect channel state information as the feedback link capacity increases to infinity -- something that is not possible with beamforming or power control alone.
Higher order sliding modes

One of the most important control problems is control under heavy uncertainty conditions. While there are a number of sophisticated methods like adaptation based on identification and observation, or absolute stability methods, the most obvious way to withstand the uncertainty is to keep some constraints by "brutal force". Indeed any strictly kept equality removes one " uncertainty dimension". The most simple way to keep a constraint is to react immediately to any deviation of the system stirring it back to the constraint by a sufficiently energetic effort. Implemented directly, the approach leads to so-called sliding modes, which become main operation modes in the variable structure systems (VSS) [55]. Having proved their high accuracy and robustness with respect to various internal and external disturbances, they also reveal their main drawback: the so-called chattering effect, i.e., dangerous high-frequency vibrations of the controlled system. Such an effect was considered as an obvious intrinsic feature of the very idea of immediate powerful reaction to the minutest deviation from the chosen constraint. Another important feature is proportionality of the maximal deviation from the constraint to the time interval between the measurements (or to the switching delay).
Differential Expression of Chemokine and Matrix Re-Modelling Genes Is Associated with Contrasting Schistosome-Induced Hepatopathology in Murine Models

The pathological outcomes of schistosomiasis are largely dependent on the molecular and cellular mechanisms of the host immune response. In this study, we investigated the contribution of variations in host gene expression to the contrasting hepatic pathology observed between two inbred mouse strains following Schistosoma japonicum infection. Whole genome microarray analysis was employed in conjunction with histological and immunohistochemical analysis to define and compare the hepatic gene expression profiles and cellular composition associated with the hepatopathology observed in S. japonicum-infected BALB/c and CBA mice. We show that the transcriptional profiles differ significantly between the two mouse strains with high statistical confidence. We identified specific genes correlating with the more severe pathology associated with CBA mice, as well as genes which may confer the milder degree of pathology associated with BALB/c mice. In BALB/c mice, neutrophil genes exhibited striking increases in expression, which coincided with the significantly greater accumulation of neutrophils at granulomatous regions seen in histological sections of hepatic tissue. In contrast, up-regulated expression of the eosinophil chemokine CCL24 in CBA mice paralleled the cellular influx of eosinophils to the hepatic granulomas. Additionally, there was greater down-regulation of genes involved in metabolic processes in CBA mice, reflecting the more pronounced hepatic damage in these mice. Profibrotic genes showed similar levels of expression in both mouse strains, as did genes associated with Th1 and Th2 responses. However, imbalances in expression of matrix metalloproteinases (e.g. MMP12, MMP13) and tissue inhibitors of metalloproteinases (TIMP1) may contribute to the contrasting pathology observed in the two strains. Overall, these results provide a more complete picture of the molecular and cellular mechanisms which govern the pathological outcome of hepatic schistosomiasis. This improved understanding of the immunopathogenesis in the murine model schistosomiasis provides the basis for a better appreciation of the complexities associated with chronic human schistosomiasis.
Setting discrete bid levels adaptively in repeated auctions

The success of an auction design often hinges on its ability to set parameters such as reserve price and bid levels that will maximize an objective function such as the auctioneer revenue. Works on designing adaptive auction mechanisms have emerged recently, and the challenge is in learning different auction parameters by observing the bidding in previous auctions. In this paper, we propose a non-parametric method for determining discrete bid levels dynamically so as to maximize the auctioneer revenue. First, we propose a non-parametric kernel method for estimating the probabilities of closing price with past auction data. Then a greedy strategy has been devised to determine the discrete bid levels based on the estimated probability information of closing price. We show experimentally that our non-parametric method is robust to changes in parameters such as the distributions of participating bidders as well as the individual bidder evaluation, and it consistently outperforms different competitors with various settings with respect to auctioneer revenue maximization.
Robust Multi-Factor Authentication for Fragile Communications

In large-scale systems, user authentication usually needs the assistance from a remote central authentication server via networks. The authentication service however could be slow or unavailable due to natural disasters or various cyber attacks on communication channels. This has raised serious concerns in systems which need robust authentication in emergency situations. The contribution of this paper is two-fold. In a slow connection situation, we present a secure generic multi-factor authentication protocol to speed up the whole authentication process. Compared with another generic protocol in the literature, the new proposal provides the same function with significant improvements in computation and communication. Another authentication mechanism, which we name stand-alone authentication, can authenticate users when the connection to the central server is down. We investigate several issues in stand-alone authentication and show how to add it on multi-factor authentication protocols in an efficient and generic way.
Fluid-Phase Pinocytosis of Native Low Density Lipoprotein Promotes Murine M-CSF Differentiated Macrophage Foam Cell Formation

During atherosclerosis, low-density lipoprotein (LDL)-derived cholesterol accumulates in macrophages to form foam cells. Macrophage uptake of LDL promotes foam cell formation but the mechanism mediating this process is not clear. The present study investigates the mechanism of LDL uptake for macrophage colony-stimulating factor (M-CSF)-differentiated murine bone marrow-derived macrophages. LDL receptor-null (LDLR−/−) macrophages incubated with LDL showed non-saturable accumulation of cholesterol that did not down-regulate for the 24 h examined. Incubation of LDLR−/− macrophages with increasing concentrations of 125I-LDL showed non-saturable macrophage LDL uptake. A 20-fold excess of unlabeled LDL had no effect on 125I-LDL uptake by wild-type macrophages and genetic deletion of the macrophage scavenger receptors CD36 and SRA did not affect 125I-LDL uptake, showing that LDL uptake occurred by fluid-phase pinocytosis independently of receptors. Cholesterol accumulation was inhibited approximately 50% in wild-type and LDLR−/− mice treated with LY294002 or wortmannin, inhibitors of all classes of phosphoinositide 3-kinases (PI3K). Time-lapse, phase-contrast microscopy showed that macropinocytosis, an important fluid-phase uptake pathway in macrophages, was blocked almost completely by PI3K inhibition with wortmannin. Pharmacological inhibition of the class I PI3K isoforms alpha, beta, gamma or delta did not affect macrophage LDL-derived cholesterol accumulation or macropinocytosis. Furthermore, macrophages from mice expressing kinase-dead class I PI3K beta, gamma or delta isoforms showed no decrease in cholesterol accumulation or macropinocytosis when compared with wild-type macrophages. Thus, non-class I PI3K isoforms mediated macropinocytosis in these macrophages. Further characterization of the components necessary for LDL uptake, cholesterol accumulation, and macropinocytosis identified dynamin, microtubules, actin, and vacuolar type H(+)-ATPase as contributing to uptake. However, Pak1, Rac1, and Src-family kinases, which mediate fluid-phase pinocytosis in certain other cell types, were unnecessary. In conclusion, our findings provide evidence that targeting those components mediating macrophage macropinocytosis with inhibitors may be an effective strategy to limit macrophage accumulation of LDL-derived cholesterol in arteries.
Soliton Management for Ultra-high Speed Telecommunications

The methodology developed provides for a systematic way to find an infinite number of the novel stable bright and dark ‘‘soliton islands’’ in a ‘’sea of solitary waves’’ of the non linear Schrödinger equation model with varying dispersion, non linearity and gain or absorption. It is shown that solitons exist only under certain conditions and the parameter functions describing dispersion, non linearity and gain or absorption inhomogeneities cannot be chosen independently. Fundamental soliton management regimes for ultra-high speed fiber optics telecommunications are discovered.
Scenario test of accelerometer-based biometric gait recognition

The goal of our research is to develop methods for accelerometer-based gait recognition, which are robust, stable and fast enough to be used for authentication on mobile devices. To show how far we are in reaching this goal we developed a new cycle extraction method, implemented an application for android phones and conducted a scenario test. We evaluated two different methods, which apply the same cycle extraction technique but use different comparison methods. 48 subjects took part in the scenario test. After enrolment they were walking for about 15 minutes on a predefined route. To get a realistic scenario this route included climbing of stairs, opening doors, walking around corners etc. About every 30 seconds the subject stopped and the authentication was started. This paper introduces the new cycle extraction method and shows the Detection Error Trade-Off-curves, error rates separated by route-section and subject as well as the computation times for enrolment and authentication on a Motorola milestone phone.
In Vivo Prediction of Vascular Susceptibility to Vascular Endothelial Growth Factor Withdrawal Magnetic Resonance Imaging of C6 Rat Glioma in Nude Mice

One of the hallmarks of tumor neovasculature is the prevalence of immature vessels manifested by the low degree of recruitment of vascular mural cells such as pericytes and smooth muscle cells. This difference in the architecture of the vascular bed provides an important therapeutic window for inflicting tumor-selective vascular damage. Here we demonstrate the application of gradient echo magnetic resonance imaging (MRI) for noninvasive in vivo mapping of vascular maturation, manifested by the ability of mature vessels to dilate in response to elevated levels of CO2. Histological alpha-actin staining showed a match between dilating vessels detected by MRI and vessels coated with smooth muscle cells. Switchable, vascular endothelial growth factor (VEGF)-overexpressing tumors (C6-pTET-VEGF rat glioma s.c. tumors in nude mice) displayed high vascular function and significant vascular damage upon VEGF withdrawal. However, damage was restricted to nondilating vessels, whereas mature dilating tumor vessels were resistant to VEGF withdrawal. Thus, MRI provides in vivo visualization of vascular maturity and prognosis of vascular obliteration induced by VEGF withdrawal.
Effects of school meals based on the New Nordic Diet on intake of signature foods: a randomised controlled trial. The OPUS School Meal Study

Abstract A New Nordic Diet (NND) was developed in the context of the Danish OPUS Study (Optimal well-being, development and health for Danish children through a healthy New Nordic Diet). Health, gastronomic potential, sustainability and Nordic identity were crucial principles of the NND. The aim of the present study was to investigate the effects of serving NND school meals compared with the usual packed lunches on the dietary intake of NND signature foods. For two 3-month periods, 834 Danish children aged 8–11 years received NND school meals or their usual packed lunches brought from home (control) in random order. The entire diet was recorded over 7 consecutive days using a validated Web-based Dietary Assessment Software for Children. The NND resulted in higher intakes during the entire week (% increase) of root vegetables (116 (95 % CI 1·93, 2·42)), cabbage (26 (95 % CI 1·08, 1·47)), legumes (22 (95 % CI 1·06, 1·40)), herbs (175 (95 % CI 2·36, 3·20)), fresh berries (48 (95 % CI 1·13, 1·94)), nuts and seeds (18 (95 % CI 1·02, 1·38)), lean fish and fish products (47 (95 % CI 1·31, 1·66)), fat fish and fish products (18 (95 % CI 1·02, 1·37)) and potatoes (129 (95 % CI 2·05, 2·56)). Furthermore, there was a decrease in the number of children with zero intakes when their habitual packed lunches were replaced by NND school meals. In conclusion, this study showed that the children increased their intake of NND signature foods, and, furthermore, there was a decrease in the number of children with zero intakes of NND signature foods when their habitual packed lunches were replaced by school meals following the NND principles.
Cluster_Based Profile Monitoring in Phase I Analysis

An innovative profile monitoring methodology is introduced for Phase I analysis. The proposed technique, which is referred to as the cluster-based profile monitoring method, incorporates a cluster analysis phase to aid in determining if non conforming profiles are present in the historical data set (HDS). To cluster the profiles, the proposed method first replaces the data for each profile with an estimated profile curve, using some appropriate regression method, and clusters the profiles based on their estimated parameter vectors. This cluster phase then yields a main cluster which contains more than half of the profiles. The initial estimated population average (PA) parameters are obtained by fitting a linear mixed model to those profiles in the main cluster. In-control profiles, determined using the Hotelling's 2 T statistic, that are not contained in the initial main cluster are iteratively added to the main cluster and the mixed model is used to update the estimated PA parameters. A simulated example and Monte Carlo results demonstrate the performance advantage of this proposed method over a current non-cluster based method with respect to more accurate estimates of the PA parameters and better classification performance in determining those profiles from an in-control process from those from an out-of-control process in Phase I.
COMMUNITY DETECTION IN SOCIAL NETWORKS: AN OVERVIEW

A social network can be defined as a set of people connected by a set of people. Social network analysis provides both a visual and a mathematical analysis of human relationship. The investigation of the community structure in the social network has been the important issue in many domains and disciplines. Community structure assumes more significance with the increasing popularity of online social network services like Facebook, MySpace, or Twitter. This paper reflects the emergence of communities that occur in the structure of social networks, represented as graphs. We have mainly discussed various community detection algorithms in real world networks in this paper. This paper represents as an overview of the community detection algorithms in social networks.