Miracle-dz/UniFAR-FTUs huggingface dataset:
Failure recovery of circulating NKG2D+CD56dimNK cells in HBV-associated hepatocellular carcinoma after hepatectomy predicts early recurrence

Dysfunction of natural killer (NK) cells has been implicated in the failure of antitumor immune responses in hepatocellular carcinoma (HCC) patients. However, the changes of NK profile in peripheral blood after surgery and tumor tissues of HCC patients, as well as the underlying reason and the significance are vague. Here, we observed that the frequencies of circulating NKG2D+CD56dimNK cells decreased significantly in HBV-related HCC and were negatively correlated with the levels of serum TGF-β and soluble MICA (sMICA). In vitro experiments confirmed that the TGF-β and sMICA in tumor tissue homogenates, as well as sMICA in HCC cells culture supernatants could reduce the frequency of NKG2D+CD56dimNK cells. In addition, in HCC patients the lower frequency of circulating NKG2D+CD56dimNK cells was associated with larger tumor size and/or higher serum GGT. Noticeably, the frequency of NKG2D+CD56dimNK cells at one month after surgery usually failed to restore in early recurrent patients, and that frequency was negatively associated with early recurrence and shorter overall survival. These results suggest that declined frequency of NKG2D+CD56dimNK cells in HCC was associated with higher TGF-β and sMICA production, and low frequency of circulating NKG2D+CD56dimNK cells at one month after surgery may predict poor prognosis of HBV-related HCC patients accepting hepatectomy.
A performance study of various brain source imaging approaches

The objective of brain source imaging consists in reconstructing the cerebral activity everywhere within the brain based on EEG or MEG measurements recorded on the scalp. This requires solving an ill-posed linear inverse problem. In order to restore identifiability, additional hypotheses need to be imposed on the source distribution, giving rise to an impressive number of brain source imaging algorithms. However, a thorough comparison of different methodologies is still missing in the literature. In this paper, we provide an overview of priors that have been used for brain source imaging and conduct a comparative simulation study with seven representative algorithms corresponding to the classes of minimum norm, sparse, tensor-based, subspace-based, and Bayesian approaches. This permits us to identify new benchmark algorithms and promising directions for future research.
Please Scroll down for Article Social Neuroscience Age-related Valence-based Reversal in Recruitment of Medial Prefrontal Cortex on a Visual Search Task Age-related Valence-based Reversal in Recruitment of Medial Prefrontal Cortex on a Visual Search Task Age-related Detection of Emotional Images

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Previous behavioral research has revealed a positivity effect that occurs with aging, with older adults focusing more on positive information and less on negative emotional stimuli as compared to young adults. Questions have been raised as to whether this effect exists in the rapid detection of information or whether it operates only at later stages of processing. In the present study, we used eye-tracking and neuroimaging methodologies to examine whether the two age groups accomplished the detection of emotional information on a visual search task using the same mechanisms. Eye-tracking results revealed no significant age differences in detection or viewing time of emotional targets as a function of valence. Despite their general similarity in task performance, neuroimaging results revealed an age-related valence-based reversal in medial prefrontal cortex (MPFC) activity, with detection of negative compared to positive targets activating the MPFC more for younger adults, and detection of positive compared to negative targets activating the MPFC more for older adults. These results suggest that age-related valence reversals in neural activity can exist even on tasks that require only relatively automatic processing of emotional information.
A Hybrid Competitive Genetic Algorithm Models in Stock Market Prediction

— Stock market prediction (SMP) plays an important role in the modern era for any economy which is on the development phase. Genetic Algorithm (GA) is an evolutionary algorithm that is useful for solving problems which are too complex in nature. This paper surveys different GA models that have been experimented in stock market prediction with special enhancement techniques used with them to improve the prediction accuracy. The classification is made in terms of GA with two layer, multilayer, neural network variants and modified evolutionary algorithms. Through the surveyed paper it is shown that the performance of GA excels when integrated with other machine learning algorithms.
Independent Directions-Based Algorithm for Classification Targets

The reported work proposes a new algorithm for classification tasks, an algorithm based on independent directions of the sample data. The classes are learned by the algorithm using the information contained by samples randomly generated from them. The learning process is based on the set of class skeletons, where the class skeleton is represented by the independent axes estimated from data. Basically, for each new sample, the recognition algorithm classifies it in the class whose skeleton is the "nearest" to this example. Comparative analysis is performed and experimentally derived conclusions concerning the performance of the proposed method are reported in the final section of the paper for signals recognition applications.
Effects of 5-aminolevulinic acid-mediated sonodynamic therapy on macrophages

Objectives Inflammatory cells exhibit elevated level of protoporphyrin IX (PpIX) after the administration of 5-aminolevulinic acid (ALA). This study aims to investigate the sonodynamic effects of ALA derived PpIX (ALA-PpIX) on macrophages, which are the pivotal inflammatory cells in atherosclerosis. Methods THP-1 derived macrophages were incubated with diffferent concentrations of ALA (0-10.0 mM), and then exposed to the ultrasound for 0-15 minutes. Fluorescence microscope and fluorescence spectrometer were performed to detect intracellular PpIX concentration. MTT assay was used for cell viability measurment. Hoechst 33342 and propidium iodide assay and flow cytometry analysis were performed to measure cell apoptosis and necrosis. Intracellular reactive oxygen species (ROS) generation and mitochondrial membrane potential (MMP) loss were assessed using fluorescence prober DCFH-DA and jc-1, respectively. Results Intracellular PpIX increased with the concentration of ALA in the incubation solution in a time dependent manner, and the most intracellular PpIX was observed at 3 hours incubation. Lower concentrations (less than 2 mM) of ALA has no influence on cell viability (more than 90% of cells survived), but sonodynamic therapy (SDT) with low concentration ALA significantly decreased the survival rate of cells, and the effect increased with both ALA concentration and ultrasound exposure time. ALA-SDT induced both cell apoptosis and necrosis, and the maximum apoptosis/necrosis ratio was observed at 6 hours after SDT with 1 mM of ALA and 5 minutes of ultrasound exposure. Flow cytometry analysis showed that ALA-SDT significantly increased late stage apoptotic cells (about 10 folds of control). Furthermore, ALA-SDT induced reactive oxygen species (ROS) generation in THP-1 macrophages immediately after the treatment and a conspicuous loss of mitochondrial membrane potential (MMP) at 6 hours, compared with that of control, ALA alone and ultrasound alone groups. Conclusions ALA-SDT exhibited synergistic apoptotic effects on THP-1 macrophages, involving excessive intracellular ROS generation and MMP loss. Therefore, ALA-SDT can be a potential treatment for atherosclerosis.
Detecting and Correcting Misconceptions with Lifelike Avatars in 3 D Learning Environments

Lifelike pedagogical agents offer significant promise for addressing a central problem posed by learning environments: detecting and correcting students’ misconceptions. By designing engaging lifelike avatars and introducing them into task-oriented 3D learning environments, we can enable them to serve a dual communication role. They can serve as students’ representatives in learning environments and simultaneously provide realtime advice to address their misconceptions. We describe a three-phase avatar-based misconception correction framework in which (1) as students navigate their avatars through 3D learning environments, a misconception detector tracks their problem-solving activities by inspecting task networks, (2) when they take sub-optimal or incorrect actions, a misconception classifier examines misconception trees to identify the most salient misconceptions, and (3) the avatars employ a misconception corrector to intervene with tailored advice. The framework has been implemented in a misconception system for the lifelike avatar of CPU CITY, a 3D learning environment testbed for the domain of fundamentals of computer architecture. In CPU CITY, students direct their lifelike avatar to navigate a 3D world consisting of a virtual computer, to transport data and address packets, and to manipulate computational devices. Informal studies with students interacting with CPU CITY suggest that the framework can is an effective tool for addressing students’ misconceptions.
High Performance Error Detection and Correction Technique for Memories Using Difference - Set Codes

As technology scales, Single Event Upsets (SEU) become more common and affect a large number of memory cells. In order to protect memories against SEUs is to make use advanced error detecting and correcting codes are used. An error detection method for difference – set cyclic codes with majority logic is presented in this paper. Majority logic decodable codes have the capability to correct a large number of errors so these codes are used in memory applications. But they require a large decoding time which affects the memory performance. The proposed fault detection technique resolves this problem. It reduces the memory access time when there is no error in the data read. In this technique the Majority Logic Decoder (MLD) itself used to detect failures, thus area become minimal and keeps the extra power consumption low.
Formal Verification of Computer Narratives

We consider modern computer narratives as deterministic fin ite automata with identified initial, winning, and losing states. We discuss various interesting tem poral properties in the context of narratives, which range from simple reachability to more complex concep ts such as the degree of “pointlessness”. These temporal properties can be useful in model checking na rratives, but first an appropriate representation is needed. We introduce the Narrative Flow Graph(NFG), a class of 1-safe Petri Net, suitable for modelling computer narratives compactly, and the higher-l evel Programmable NFG(PNFG) language that compiles down to NFGs. We show how NFGs can be automatica lly encoded as transition relations for the NuSMV model checker, and use high-level knowledge fr om the PNFG language to reduce the number of boolean variables required. We finally provide an e xperimental analysis of small, medium, and large narratives.
Oxidative stress in schizophrenia

The present study was conducted to verify the oxidative stress status in schizophrenia. Malondialdehyde, reduce glutathione, superoxide dismutase, and vitamin C levels were measured in sera of seventy schizophr enic patients and thirty healthy individuals. The statistical analysis (students t- test) showed a significant (p<0.005) increase of malondialdehyde (MDA) while a significant (p<0.005) decrease in reduce glutathione (GSH) also a significant (p<0.005) decr ease in superoxide dismutase and a significant (p<0.005) decrease in vitamin C levels in schizophrenic patients when compared with those of the control group. The evalu ation of sex differences effect on oxidative stress in schizophrenic patients show a s ignificant (p<0.025) increase in MDA but a significant (p<0.005) decrease in GSH and a s ignificant (p<0.025) decrease in SOD in female in comparison to male groups. According to the symptoms of schizophrenia show there are a significant (p<0.05) increase in MDA in positive symptom when compare to negative symptoms while a significant (p<0.005) decrease in SOD and GSH in negative symptom when compare to positive symptoms The results indicate that schizophrenia is associa ted with oxidative stress. And it appears that when the case gets worse the oxidative stress parameters will dependently changes. So schizophrenia is a sever psychiatric di sorder and since there is an evidence that an excessive free radicals production or oxidative stress may be involved in the pathophysiology of schizophrenic patient. So that t he excess quantities of ROS that are produced by schizophrenic patients may overcome the host antioxidant defenses and cause oxidative stress. Keywords oxidative stress, free radicals, MDA, GSH, SOD, vi tamin C, Antioxidants, Schizophrenia.
Automated detection and cell density assessment of keratocytes in the human corneal stroma from ultrahigh resolution optical coherence tomograms

Keratocytes are fibroblast-like cells that maintain the optical clarity and the overall health of the cornea. The ability to measure precisely their density and spatial distribution in the cornea is important for the understanding of corneal healing processes and the diagnostics of some corneal disorders. A novel computerized approach to detection and counting of keratocyte cells from ultra high resolution optical coherence tomography (UHR-OCT) images of the human corneal stroma is presented. The corneal OCT data is first processed using a state-of-the-art despeckling algorithm to reduce the effect of speckle on detection accuracy. A thresholding strategy is then employed to allow for improved delineation of keratocyte cells by suppressing similarly shaped features in the data, followed by a second-order moment analysis to identify potential cell nuclei candidates. Finally, a local extrema strategy is used to refine the candidates to determine the locations and the number of keratocyte cells. Cell density distribution analysis was carried in 3D UHR-OCT images of the human corneal stroma, acquired in-vivo. The cell density results obtained using the proposed novel approach correlate well with previous work on computerized keratocyte cell counting from confocal microscopy images of human cornea.
A two-continua approach to Eulerian simulation of water spray

Physics based simulation of the dynamics of water spray - water droplets dispersed in air - is a means to increase the visual plausibility of computer graphics modeled phenomena such as waterfalls, water jets and stormy seas. Spray phenomena are frequently encountered by the visual effects industry and often challenge state of the art methods. Current spray simulation pipelines typically employ a combination of Lagrangian (particle) and Eulerian (volumetric) methods - the Eulerian methods being used for parts of the spray where individual droplets are not apparent. However, existing Eulerian methods in computer graphics are based on gas solvers that will for example exhibit hydrostatic equilibrium in certain scenarios where the air is expected to rise and the water droplets fall. To overcome this problem, we propose to simulate spray in the Eulerian domain as a two-way coupled two-continua of air and water phases co-existing at each point in space. The fundamental equations originate in applied physics and we present a number of contributions that make Eulerian two-continua spray simulation feasible for computer graphics applications. The contributions include a Poisson equation that fits into the operator splitting methodology as well as (semi-)implicit discretizations of droplet diffusion and the drag force with improved stability properties. As shown by several examples, our approach allows us to more faithfully capture the dynamics of spray than previous Eulerian methods.
Complementary quantity in Swedish dialects

The current study is undertaken within the project Swedia 2000, one objective of which is the development of a quantity typology for Swedish dialects. To that end, a series of studies has hitherto been undertaken. Strangert and Wretling (2002), Schaeffler, Wretling and Strangert (2002) and Schaeffler and Wretling (2002) report on temporal and/or spectral aspects of quantity distinctions in Northern dialects of Sweden and Swedish-speaking areas of Finland. The studies all depart from the standard phonologic analysis of Swedish (Elert, 1964) according to which there is a length distinction in vowels as well as consonants and moreover, a complementary pattern of the vowel and immediately following consonant in stressed syllables resulting in sequences of V:C and VC:, respectively. Also, in a recent study, Schaeffler and Wretling (2003) employing a top-down type of approach, related quantity data to a traditional classification of dialect areas. In contrast, the approach here is bottom-up, starting out from data without any pre-determined idea of dialect areas. We aim at an overview of complementary quantity manifestations based on speakers from close to 70 locations all over Sweden and the Swedish-speaking areas in Finland.
A Machine Learning-Based Approach to Estimate the CPU-Burst Time for Processes in the Computational Grids

The implementation of CPU-Scheduling algorithms such as Shortest-Job-First (SJF) and Shortest Remaining Time First (SRTF) is relying on knowing the length of the CPU-bursts for processes in the ready queue. There are several methods to predict the length of the CPU-bursts, such as exponential averaging method, however these methods may not give an accurate or reliable predicted values. In this paper, we will propose a Machine Learning (ML) based approach to estimate the length of the CPU-bursts for processes. The proposed approach aims to select the most significant attributes of the process using feature selection techniques and then predicts the CPU-burst for the process in the grid. ML techniques such as Support Vector Machine (SVM) and K-Nearest Neighbors (K-NN), Artificial Neural Networks (ANN) and Decision Trees (DT) are used to test and evaluate the proposed approach using a grid workload dataset named "GWA-T-4 Auver Grid". The experimental results show that there is a strength linear relationship between the process attributes and the burst CPU time. Moreover, K-NN performs better in nearly all approaches in terms of CC and RAE. Furthermore, applying attribute selection techniques improves the performance in terms of space, time and estimation.
Multiphasic Analysis of Embryonic Mortality in Chickens 1

Infertility and embryonic mortality are economically important for the commercial broiler industry because they are components of hatchability. Embryonic mortality in chickens is not uniformly distributed over the course of incubation; two phases of embryonic mortality are characteristic of chicken development. The objective of this paper was to develop a mathematical model to assess infertility and to characterize the distribution over time of embryonic mortality in chickens. A model was constructed based on evidence in the literature for multiple phases of embryonic mortality before and during incubation. A multiphasic model, with two phases, included parameters for the proportion of eggs that were infertile and the proportion
A breakthrough for prepaid payment: End to end token exchange and management using secure SSL channels created by EAP-TLS smart cards

In this paper we present an innovative architecture for prepaid services. Digital tokens are securely exchanged between EAP-TLS smart cards used both by merchant and customer. We describe the global framework that comprises a back-office server delivering tokens, a front-office server collecting tokens from merchant terminal, merchants and customers equipped with smart cards. We detail data exchange choreography and discuss performances issues for the experimental platform built with commercial devices.
A CMOS multi-parameter biochemical microsensor with temperature control and signal interfacing

A fully-integrated microsensor chip allows continuous monitoring of concentrations of blood gases (pH, pO/sub 2/, pCO/sub 2/), ions, and biomolecules, and a conductometric measurement. The chip monitors 7 different chemical properties and includes temperature control and an EPROM. It occupies 25.7 mm/sup 2/ in a standard 1.2 /spl mu/m CMOS process including chemical sensor postprocessing and operates at 5 V.
Theories of Emotion Regulation

Emotions refer to mental states that are spontaneously generated, can be positive or negative, fleeting or more prolonged, and can be experienced at varying levels of intensity. Emotions are also under cognitive control, whereby strategies for emotion regulation mean that they may be experienced more or less intensely. A failure to regulate emotional states adequately has been linked with antisocial behaviour and sexual offending in particular. This chapter discusses the evidence for emotion regulation difficulties in sexual offenders and describes the ways in which mindfulness meditation and biofeedback techniques may be used to enhance the ability for emotion regulation in the treatment of sexual offenders. The use of these techniques has been shown to affect the functioning of the prefrontal cortex and the amygdala, the critical structures involved in emotion regulation, and has been linked with improved regulation of affective states in clinical studies. Keywords: emotion regulation; heart rate variability; heart rate variability biofeedback; mindfulness; sexual offender; treatment
Mobility assisted opportunistic scheduling for downlink transmissions in cellular data networks

The paper presents an online opportunistic scheduling algorithm for downlink transmission in a time-slotted shared wireless network that combines channel fluctuation and user mobility information in the decision rule. The algorithm is a general scheduling scheme and adapts well with any utility function for elastic traffic. For finite workload service demands, the scheme uses less completion time than the max-rate scheduling scheme. Under moderate load conditions, it gives time savings of up to 10%. For infinite backlog service demands, the proposed algorithm performs better than the proportional fair algorithm. Simulation results illustrate the usefulness of the proposed scheme for elastic traffic and moderate load conditions.