Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of Chronic Fatigue Syndrome and Fibromyalgia with D-Ribose- An Open-label, Multicenter Study

Objectives: Chronic Fatigue Syndrome and Fibromyalgia (CFS/FMS) are debilitating syndromes affecting ~2- 4% of the population. Although they are heterogeneous conditions associated with many triggers, they appear to have the common pathology of being associated with impaired energy metabolism. As D-ribose has been shown to increase cellular energy synthesis, and was shown to significantly improve clinical outcomes in CFS/FMS in an earlier study, we hypothesized that giving D-ribose would improve function in CFS/FMS patients. Design, Location, and Subjects: An open-label, unblinded study in which 53 US clinics enrolled 257 patients who had been given a diagnosis of CFS/FMS by a health practitioner. Interventions: All subjects were given D-ribose (Corvalen￻), a naturally occurring pentose carbohydrate, 5-g TID for 3 weeks.
VorAIS: A Multi-Objective Voronoi Diagram-based Artificial Immune System

This paper introduces the Voronoi diagram-based Artificial Immune System (VorAIS). VorAIS models the self/non-self using a Voronoi diagram that determines which areas of the problem domain correspond to self or to non-self. The diagram is evolved using a multi-objective bio-inspired approach in order to conjointly optimize various classification metrics (accuracy, recall and specificity). VorAIS is experimentally validated, first on standard classification problems, then on the well-known NSL-KDD dataset for anomaly detection where it favorably compares with other AIS approaches.
Global Profiling of the Cell Surface Proteome of Cancer Cells Uncovers an Abundance of Proteins with Chaperone Function*

There is currently limited data available pertaining to the global characterization of the cell surface proteome. We have implemented a strategy for the comprehensive profiling and identification of surface membrane proteins. This strategy has been applied to cancer cells, including the SH-SY5Y neuroblastoma, the A549 lung adenocarcinoma, the LoVo colon adenocarcinoma, and the Sup-B15 acute lymphoblastic leukemia (B cell) cell lines and ovarian tumor cells. Surface membrane proteins of viable, intact cells were subjected to biotinylation then affinity-captured and purified on monomeric avidin columns. The biotinylated proteins were eluted from the monomeric avidin columns as intact proteins and were subsequently separated by two-dimensional PAGE, transferred to polyvinylidene difluoride membranes, and visualized by hybridization with streptavidin-horseradish peroxidase. Highly reproducible, but distinct, two-dimensional patterns consisting of several hundred biotinylated proteins were obtained for the different cell populations analyzed. Identification of a subset of biotinylated proteins among the different cell populations analyzed using matrix-assisted laser desorption ionization and tandem mass spectrometry uncovered proteins with a restricted expression pattern in some cell line(s), such as CD87 and the activin receptor type IIB. We also identified more widely expressed proteins, such as CD98, and a sushi repeat-containing protein, a member of the selectin family. Remarkably, a set of proteins identified as chaperone proteins were found to be highly abundant on the cell surface, including GRP78, GRP75, HSP70, HSP60, HSP54, HSP27, and protein disulfide isomerase. Comprehensive profiling of the cell surface proteome provides an effective approach for the identification of commonly occurring proteins as well as proteins with restricted expression patterns in this compartment.
FROBENIUS SPLITTING FOR

This thesis presents an expository account of the use of Frobenius splitting techniques in the study of Schubert varieties. After developing the basic theory of Frobenius splitting, we show that the Schubert and Bott-Samelson varieties are split and use this to derive geometric consequences in arbitrary characteristic. The main result highlighted is that Schubert varieties are normal, Cohen-Macaulay, and have rational resolutions. In addition, we give a proof of the Demazure character formula.
Activity-centric support for weakly-structured business processes

Knowledge-intensive tasks are a blind spot for business process management systems, as these tasks are executed in an unsupervised, highly individual manner. Hence, individual experience is not disseminated and task execution largely depends on implicit knowledge. In this paper we present a framework, realizing situation-specific and personalized task execution support for knowledge-intensive tasks in business processes. As a core concept we suggest activity scheme: a structure capturing a probabilistic task execution model. Activity schemes seamlessly integrate the organizational business process with the individual task execution process based on personalization and generalization of user interactions in the working applications.
Online estimation of IGBT junction temperature (Tj) using gate-emitter voltage (Vge) at turn-off

The paper presents a novel method for online estimation of the junction temperature (Tj) of semiconductor chips in IGBT modules, based on evaluating the gate-emitter voltage (Vge) during the IGBT switch off process. It is shown that the Miller plateau width (in the Vge waveform) depend linearly on the junction temperature of the IGBT chips. Hence, a method can be proposed for estimating the junction temperature even during converter operation - without the need of additional thermal sensors or complex Rth network models. A measurement circuit was implemented at gate level to measure the involved time duration and its functionality was demonstrated for different types of IGBT modules.
Characterization of Fibroblast Clones from Periodontal Granulation Tissue in vitro

Connective tissues are known to be composed of heterogeneous fibroblast subpopulations. The significance of this heterogeneity in different physiological and pathological conditions is poorly understood. Granulation tissue is formed in connective tissue during wound healing, chronic inflammation, and certain pathological conditions. In this study, heterogeneity of fibroblasts from granulation tissue was investigated by cell-cloning techniques. Granulation-tissue fibroblasts (GTFs) from both chronically inflamed periodontal lesions and healing wound granulation tissue behaved similarly. GTFs showed a more pronounced decrease in proliferative capacity with increasing cumulative population doubling levels (CPDLs) and 30-40% lower cloning efficiency compared with normal gingival fibroblasts (HGFs). Morphologically, cells in GTF cultures were mainly large, whereas HGFs were mainly small in size. Both cell-line types showed heterogeneity in cell morphology. Clones composed of large stellate-like cells predominated in GTF cultures, whereas clones composed of small spindle-shaped or epithelioid cells predominated in HGF cultures. In both cell-line types, the proportion of clones composed of large cells increased with increasing CPDL. These findings show that the properties of the fibroblasts changed during their in vitro life spans. The finding that normal connective tissue and granulation tissues contain morphologically distinct fibroblast clones in different proportions suggests that local factors could stimulate local fibroblasts to differentiate into GTFs. Alternatively, local factors could select some fibroblast subpopulations to overgrow the others to form granulation tissue.
Constraint programming for random testing of a trading system

Financial markets use complex computer trading systems whose failures can cause serious economic damage, making reliability a major concern. Automated random testing has been shown to be useful in finding defects in these systems, but its inherent test oracle problem (automatic generation of the expected system output) is a drawback that has typically prevented its application on a larger scale. Two main tasks have been carried out in this thesis as a solution to the test oracle problem. First, an independent model of a real trading system based on constraint programming, a method for solving combinatorial problems, has been created. Then, the model has been integrated as a true test oracle in automated random tests. The test oracle maintains the expected state of an order book throughout a sequence of random trade order actions, and provides the expected output of every auction triggered in the order book by generating a corresponding constraint program that is solved with the aid of a constraint programming system. Constraint programming has allowed the development of an inexpensive, yet reliable test oracle. In 500 random test cases, the test oracle has detected two system failures. These failures correspond to defects that had been present for several years without being discovered neither by less complete oracles nor by the application of more systematic testing approaches. The main contributions of this thesis are: (1) empirical evidence of both the suitability of applying constraint programming to solve the test oracle problem and the effectiveness of true test oracles in random testing, and (2) a first attempt, as far as the author is aware, to model a non-theoretical continuous double auction using constraint programming.
Suppression of neurocognitive damage in LP‐BM5‐infected mice with a targeted deletion of the TNF‐α gene

Brain levels of TNF‐α increase in many inflammatory conditions, including HIV‐1 infection, and may contribute to neurodegenerative processes. The paucity of agents that can selectively and potently block TNF‐α processing or its receptors has led us to investigate the role of TNF‐α in chronic neurodegeneration associated with retroviral infection using mice with targeted deletions of the TNF‐α gene. Infection of wild‐type C57BL/6 mice with the LP‐BM5 murine leukemia retrovirus mixture leads to the development of a severe immunodeficiency as well as cognitive deficits and neuronal damage. TNF‐α‐(‐/‐) mice infected with LP‐BM5 developed a systemic immunopathology indistinguishable in severity from that observed in contemporaneously infected wild‐type mice. In contrast, the performance of infected TNF‐α‐(‐/‐) mice in the γ‐maze and Morris water maze was not different from that of uninfected TNF‐α‐(‐/‐) mice. The extent of glial activation in the striatum, as indicated by the increase in density of peripheral benzodiazepine receptors, was equivalent in both groups of LP‐BM5‐infected mice. However, the decrease in striatal MAP‐2 expression, a marker of neurodegeneration observed in infected wild‐type mice, was not found in infected TNF‐α‐(‐/‐) mice. While the loss of TNF‐α appeared to have no effect on the course or severity of the central or peripheral immunopathology resulting from LP‐BM5 infection, the behavioral and biochemical manifestations were substantially curtailed in the TNF‐α‐(‐/‐) mice. These findings directly support a role for TNF‐α in the neurodegenerative processes associated with viral infections such as HIV‐1. —Iida, R. , Saito, K. , Yamada, K. , Basile, A. S. , Sekikawa, K. , Takemura, M. , Fujii, Wada, H. H. , Seishima, M. , Nabeshima, T. Suppression of neurocognitive damage in LP‐BM5‐infected mice with a targeted deletion of the TNF‐α gene. FASEBJ. 14, 1023–1031 (2000)
Autonomous spectrum sharing in heterogeneous White Space networks

Regulation of cognitive radio access to spatially unused portions of TV spectrum (TV White Spaces (TVWS)) via a geolocation database was recently finalized in the US and is under way in the UK. Regulators elsewhere are also evaluating secondary use of TV and other bands. The question of how multiple potentially competing networks should share the TVWS spectrum is yet to be addressed. This is an important challenge as future deployment scenarios are expected to involve a heterogeneous mix of low-power and high-power, narrow-band and wide-band systems. This paper investigates through quantitative modelling aspects of heterogeneous spectrum sharing, taking as example TVWS sharing among low-power, e.g., the IEEE 802.11af standard, and high-power, e.g., the IEEE 802.22 and Weightless standards.
Alteration of the Systemic and Microcirculation by a Single Oral Dose of Flavan-3-Ols

Several systematic reviews have reported that flow mediated dilatation (FMD) was significantly increased in subjects after ingestion of chocolate that contains flavan-3-ols; however, the mechanisms responsible for this effect are not clear. In this study, we evaluated the effects of a single oral dose of flavan-3-ols on the systemic circulation and microcirculation in the cremaster muscle using intravital video microscopy in vivo. The cremaster muscle in rats was spread over a plastic chamber and a gastric tube was placed into the stomach. Blood flow in the cremasteric artery was determined using a laser Doppler flowmeter, while blood pressure and heart rate were measured by the tail-cuff method. Red blood cell velocity in arterioles and blood flow in the artery were significantly increased 5 min after the administration of 10 mg/kg flavan-3-ols compared with distilled water treatment. The number of capillaries recruited in the cremaster muscle was also significantly increased 15 min after treatment. Microscopic observation confirmed that increased shear stress on endothelial cells was maintained during the measurement period. The mean arterial blood pressure and heart rate were also significantly elevated soon after administration and returned to baseline before the end of the observation period. Plasma nitrate and nitrite levels, and NO phosphorylation of aortic tissue were significantly increased at 60 min after administration of flavan-3-ols. According to these results, a single oral dose of flavan-3-ols elevates blood pressure and flow transiently, and these effects induce NO production through increased shear stress on endothelial cells.
Comparison of filters for the detection of point sources in Planck simulations

We study the detection of extragalactic point sources in 2D flat simulations for all the frequencies of the forthcoming ESA’s Planck mission. In this work, we have used the most recent available templates of the microwave sky: as for the diffuse Galactic components and the Sunyaev‐Zel’dovich clusters we have used the ‘Plank Reference Sky Model’; as for the extragalactic point sources, our simulations ‐ which comprise all the source populations relevant in this frequency interval ‐ are based on up-to-date cosmological evolution models for sources. To consistently compare the capabilities of different filters for the compilation of ‐ hopefully ‐ the most complete blind catalogue of point sources, we have obtained three catalogues by filtering the simulated sky maps with: the matched filter (MF), the Mexican Hat Wavelet (MHW1) and the Mexican Hat Wavelet 2 (MHW2), the first two members of the Mexican Hat Wavelet Family. For the nine Planck frequencies we show the number of real and spurious detections and the percentage of spurious detections at different flux detection limits as well as the completeness level of the catalogues and the average errors in the estimation of the flux density of detected sources. Allowing a 5 per cent of spurious detections, we obtain the following number of detections by filtering with the MHW2 an area equivalent to half of the sky: 580 (30 GHz), 342 (44 GHz), 341 (70 GHz), 730 (100 GHz), 1130 (143 GHz), 1233 (217 GHz), 990 (353 GHz), 1025 (545 GHz) and 3183 (857 GHz). Our current results indicate that the MF and the MHW2 yield similar results, whereas the MHW1 performs worse in some cases and especially at very low fluxes. This is a relevant result, because we are able to obtain comparable results with the well-known MF and with this specific wavelet, the MHW2, which is much easier to implement and use.
Visualizing leukocyte trafficking in the living brain with 2-photon intravital microscopy

Intravital imaging of the superficial brain tissue in mice represents a powerful tool for the dissection of the cellular and molecular cues underlying inflammatory and infectious central nervous system (CNS) diseases. We present here a step-by-step protocol that will enable a non-specialist to set up a two-photon brain-imaging model. The protocol offers a two-part approach that is specifically optimized for imaging leukocytes but can be easily adapted to answer varied CNS-related biological questions. The protocol enables simultaneous visualization of fluorescently labeled immune cells, the pial microvasculature and extracellular structures such as collagen fibers at high spatial and temporal resolution. Intracranial structures are exposed through a cranial window, and physiologic conditions are maintained during extended imaging sessions via continuous superfusion of the brain surface with artificial cerebrospinal fluid (aCSF). Experiments typically require 1–2 h of preparation, which is followed by variable periods of immune cell tracking. Our methodology converges the experience of two laboratories over the past 10 years in diseased animal models such as cerebral ischemia, lupus, cerebral malaria, and toxoplasmosis. We exemplify the utility of this protocol by tracking leukocytes in transgenic mice in the pial vessels under steady-state conditions.
Network-Based Buffer Overflow Detection by Exploit Code Analysis

Buffer overﬂow attacks continue to be a major security problem and detecting attacks of this nature is therefore crucial to network security. Signature based network based intrusion detection systems (NIDS) compare network trafﬁc to signatures modelling suspicious or attack trafﬁc to detect network attacks. Since detection is based on pattern matching, a signature modelling the attack must exist for the NIDS to detect it, and it is therefore only capable of detecting known attacks. This paper proposes a method to detect buffer overﬂow attacks by parsing the payload of network packets in search of shellcode which is the remotely executable component of a buffer overﬂow attack. By analysing the shellcode it is possible to determine which system calls the exploit uses, and hence the operation of the exploit. Current NIDS-based buffer overﬂow detection techniques mainly rely upon speciﬁc signatures for each new attack. Our approach is able to detect previously unseen buffer overﬂow attacks, in addition to existing ones, without the need for speciﬁc signatures for each new attack. The method has been implemented and tested for buffer overﬂow attacks on Linux on the Intel x86 architecture using the Snort NIDS.
Fundamental Design Issues for the Future

The Internet has been a startling and dramatic success. However, multimedia applications, with their novel traac characteristics and service requirements, pose an interesting challenge to the technical foundations of the Internet. In this paper we address some of the fundamental architectural design issues facing the future Internet. In particular, we discuss whether the Internet should adopt a new service model, how this service model should be invoked, and whether this service model should include admission control. These architectural issues are discussed in a nonrigorous manner, through the use of a utility function formulation and some simple models. While we do advocate some design choices over others, the main purpose here is to provide a framework for discussing the various architectural alternatives.
A variational level set method for multiphase image segmentation

A novel multiphase image segmentation model under variational level set method framework is presented in this paper. The energy functional includes three parts: the first one is region-based component resulted from maximum a posterior probability of image partition, the second one is based on minimum geodesic active contours, the third one comes from the enforcement of level set functions as signed distance functions to avoid re-initialization. New characteristic functions for 2N regions are designed based on N level set functions and modified Heaviside functions. A semi-implicit finite difference scheme is presented for numerical solution of the corresponding evolution equations of level set functions. Some multiphase image segmentation examples are given to validate the model presented in this paper.
Predictive pattern analysis using SOM in medical data sets for medical treatment service

This paper proposes a new method of patterns analysis using SOM in medical data sets for medical treatment service under ubiquitous computing environment which is required by real time accessibility and agility. In this paper, it is necessary for us to classify disease patterns in the medical historical record to join the information of patient, using SOM neural network with input vectors of different features, disease code, input factors in order to take the medical treatment service in medical data sets, to reduce patients' search effort to get the information of diagnosis for recovering their health and to improve the rate of accuracy. To verify improved performance, we make experiments with dataset collected in medical center.
Statistical Inference for Time-varying Arch Processes 1

In this paper the class of ARCH(∞) models is generalized to the nonstationary class of ARCH(∞) models with time-varying coefficients. For fixed time points, a stationary approximation is given leading to the notation " locally stationary ARCH(∞) process. " The asymptotic properties of weighted quasi-likelihood estimators of time-varying ARCH(p) processes (p < ∞) are studied, including asymp-totic normality. In particular, the extra bias due to nonstationarity of the process is investigated. Moreover, a Taylor expansion of the nonstationary ARCH process in terms of stationary processes is given and it is proved that the time-varying ARCH process can be written as a time-varying Volterra series. 1. Introduction. To model volatility in time series, Engle [6] introduced the ARCH model where the conditional variance is stochastic and dependent on past observations. The ARCH model and several of its related models have gained widespread recognition because they model quite well the volatility in financial markets over relatively short periods of time (cf. [3, 13]). However, underlying all these models is the assumption of stationar-ity. Now given the changing pace of the world's economy, modeling financial returns over long intervals using stationary time series models may be inappropriate. It is quite plausible that structural changes in financial time series may occur, causing the time series over long intervals to deviate significantly from stationarity. It is therefore plausible that, by relaxing the assumption of stationarity in an adequate way, we may obtain a better fit. In this direction, Drees and St˘ aric˘ a [5] have proposed the simple nonlinear model X t = µ + σ(t)Z t , where Z t are independent, identically distributed random variables and σ(·) is a smooth function, which they estimate using
Keywords Extraction, Document Similarity and Categorization

With the advent of Internet since 1990’s, we have seen a tremendous growth in the volume of online text documents available on the Internet, news sources, and company-wide intranets. There is increasingly need for tools to deal with text documents. This white paper briefly presents the different perspectives of document categorization, the document similarity, and keywords extraction also is approached. We discuss the popular algorithms.