Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex pattern of Th1 and Th2 activation with a preferential increase of autoreactive Th1 cells in BALB/c mice with proteoglycan (aggrecan)‐induced arthritis

The central role of CD4+ T cells and the balance between T helper (Th) subpopulations in the pathogenesis of autoimmune diseases have been extensively studied. Proteoglycan (aggrecan)‐induced arthritis (PGIA) is a murine model for rheumatoid arthritis (RA), which is characterized by a Th1 dominance at the onset of the disease. In addition to CD4+ T cells, antigen‐presenting B cells and autoantibodies seem to play an important role in the development and regulation of PGIA. To identify proteoglycan‐specific CD4+ T cell subsets and Th1‐ and Th2‐supported antibody isotypes during the progression of PGIA, spleen cells of proteoglycan‐immunized BALB/c mice were harvested at different times of immunization, and at different stages of the disease, and their cytokine production and antigen‐specific antibody isotype profiles were determined by enzyme‐linked immunospot (ELISPOT) assays. Both Th1 and Th2 cytokine‐producing cells, with the predominance of IL‐4/IL‐5‐secreting cells, were detected during the prearthritic stage, and a shift toward a Th1 dominance was observed at the time of onset of arthritis. Tissue homogenates of acutely inflamed joints contained significantly higher levels of interferon‐gamma than IL‐4. The prearthritic period and both the acute and chronic phases of joint inflammation were characterized by IgG1 dominance in the sera and this correlated with the number of IgG1‐secreting B cells in the spleen. However, the ratio of autoreactive IgG1/IgG2a‐secreting cells decreased in arthritic animals. These results indicate the activation and possible regulatory roles of both Th1 and Th2 subsets in the autoimmune process, with the necessity of a relative increase of autoreactive Th1 cells for the induction of joint inflammation.
Cloning and Characterisation of Multiple Ferritin Isoforms in the Atlantic Salmon (Salmo salar)

Ferritin is a highly-conserved iron-storage protein that has also been identified as an acute phase protein within the innate immune system. The iron-storage function is mediated through complementary roles played by heavy (H)-chain subunit as well as the light (L) in mammals or middle (M)-chain in teleosts, respectively. In this study, we report the identification of five ferritin subunits (H1, H2, M1, M2, M3) in the Atlantic salmon that were supported by the presence of iron-regulatory regions, gene structure, conserved domains and phylogenetic analysis. Tissue distribution analysis across eight different tissues showed that each of these isoforms is differentially expressed. We also examined the expression of the ferritin isoforms in the liver and kidney of juvenile Atlantic salmon that was challenged with Aeromonas salmonicida as well as in muscle cell culture stimulated with interleukin-1β. We found that each isoform displayed unique expression profiles, and in certain conditions the expressions between the isoforms were completely diametrical to each other. Our study is the first report of multiple ferritin isoforms from both the H- and M-chains in a vertebrate species, as well as ferritin isoforms that showed decreased expression in response to infection. Taken together, the results of our study suggest the possibility of functional differences between the H- and M-chain isoforms in terms of tissue localisation, transcriptional response to bacterial exposure and stimulation by specific immune factors.
Nonlinear Perturbation Control for Magnetic Transducers

Stringent performance criteria often required in many smart material applications necessitates the need for robust control designs. Moderate to large field inputs typically introduce nonlinear, hysteretic constitutive behavior which degrades performance when linear control theory is implemented. In this paper, a hybrid nonlinear optimal control design is numerically implemented on a Terfenol-D magnetostrictive actuator to track a reference trajectory in operating regimes where nonlinear, hysteretic constitutive behavior is present. The control design incorporates perturbation feedback around an optimal open loop trajectory. The optimal open loop trajectory is computed off-line using a homogenized energy model to predict nonlinear and hysteretic constitutive behavior. The perturbation feedback is implemented using classic proportional-integral (PI) control to improve robustness to operating uncertainties. The hybrid nonlinear control design is compared to classic PI control to illustrate where improvements are achieved
Regulation of KChIP2 potassium channel β subunit gene expression underlies the gradient of transient outward current in canine and human ventricle

Expression of four members of the KChIP family of potassium channel β subunits was examined in canine heart. Only one member of the gene family, KChIP2, was expressed in heart. There was a steep gradient of KChIP2 mRNA expression across the canine ventricular free wall. KChIP2 mRNA was 25‐fold more abundant in the epicardium than in the endocardium, and this gradient paralleled the gradient in transient outward current (Ito) expression. In contrast, Kv4.3 potassium channel α subunit mRNA was expressed at equal levels across the ventricular wall. There was no difference in the pharmacological sensitivity of epicardial and endocardial Ito channels to flecainide, suggesting that the current is produced by the same channel in the two tissues. A similar gradient of KChIP2 expression was found across the ventricular wall of human heart, but not rat heart. It is concluded that transcriptional regulation of the KChIP2β subunit gene, rather than the Kv4.3α subunit gene, is the primary determinant regulating the transmural gradient of Ito expression in the ventricular free wall of canine and human heart.
A Lightweight onthe-fly Capitalization System for Automatic Speech Recognition

This paper describes a lightweight method for capitalizing speech transcriptions. Several resources were used, including a lexicon, newspaper written corpora and speech transcriptions. Different approaches were tested both generative and discriminative: finite state transducers, automatically built from Language Models; and maximum entropy models. Evaluation results are presented both for written newspaper corpora and speech transcriptions of broadcast news corpora.
TODIM and TOPSIS with Z-numbers

In this paper, we present an approach that can handle Z-numbers in the context of multi-criteria decision-making problems. The concept of Z-number as an ordered pair Z=(A, B) of fuzzy numbers A and B is used, where A is a linguistic value of a variable of interest and B is a linguistic value of the probability measure of A. As human beings, we communicate with each other by means of natural language using sentences like “the journey from home to university most likely takes about half an hour. ” The Z-numbers are converted to fuzzy numbers. Then the Z-TODIM and Z-TOPSIS are presented as a direct extension of the fuzzy TODIM and fuzzy TOPSIS, respectively. The proposed methods are applied to two case studies and compared with the standard approach using crisp values. The results obtained show the feasibility of the approach.
A wearable textile antenna for wireless power transfer by magnetic resonance

The paper presents a wearable textile antenna embroidered on a fabric for wireless power transfer systems. A planar spiral coil was generated with the conductive thread on a cotton substrate, and was connected to a rectifier circuit fabricated on flexible polyethylene terephthalate film to constitute a bendable receiver by the magnetic resonance. At a resonance frequency of 6.78 MHz, the proposed system could achieve −5.51 dB transfer efficiency and 12.75 mW power transmission at a distance of 15 cm. It was also demonstrated that the resonance frequency and transmitted power of the proposed system could be maintained as the same even when the system was bent conformingly to the surface curvature of the human body model for a bending radius up to 50 mm or larger.
Learning convolutive features for storage and transmission between networked sensors

Discovering an efficient representation that reflects the structure of a signal ensemble is a requirement of many Machine Learning and Signal Processing methods, and gaining increasing prevalence in sensing systems. This type of representation can be constructed by Convolutive Non-negative Matrix Factorization (CNMF), which finds parts-based convolutive representations of non-negative data. However, convolutive extensions of NMF have not yet considered storage efficiency as a side constraint during the learning procedure. To address this challenge, we describe a new algorithm that fuses ideas from the 1) parts-based learning and 2) integer sequence compression literature. The resulting algorithm, Storable NMF (SNMF), enjoys the merits of both techniques: it retains the good-approximation properties of CNMF while also taking into account the size of the symbol set which is used to express the learned convolutive factors and activations. We argue that CNMF is not as amenable to transmission and storage, in networked sensing systems, as SNMF. We demonstrate that SNMF yields a compression ratio ranging from 10:1 up to 20:1, depending on the signal, which gives rise to a similar bandwidth saving for networked sensors.
Analyzing Reading Behavior by Blog Mining

This paper presents a study of the various aspects of blog reading behavior. The analyzed data are obtained from a Japanese weblog hosting service, Doblog. Four kinds of social networks are generated and analyzed: citation, comment, trackback, and blogroll networks. In addition, the user log data are used to identify readership relations among bloggers. After analysis of more than 50,000 users for about two years, we reveal some interactions between social relations and readership relations. We first show that bloggers read other weblogs on a regular basis (50% of weblogs that are read at least three times are read every five times a user logs in). We call this relation a regular reading relation (RR relation). Then, prediction of RR relations is done using features from the four kinds of social networks. Lastly, information diffusion on RR relations is analyzed and characterized. Results of this study show that the blogs in RR relations have an important role in bloggers' activities. We find the features which have a correlation with RR relations.
Enhancing automatically discovered multi-level acoustic patterns considering context consistency with applications in spoken term detection

This paper presents a novel approach for enhancing the multiple sets of acoustic patterns automatically discovered from a given corpus. In a previous work it was proposed that different HMM configurations (number of states per model, number of distinct models) for the acoustic patterns form a two-dimensional space. Multiple sets of acoustic patterns automatically discovered with the HMM configurations properly located on different points over this two-dimensional space were shown to be complementary to one another, jointly capturing the characteristics of the given corpus. By representing the given corpus as sequences of acoustic patterns on different HMM sets, the pattern indices in these sequences can be relabeled considering the context consistency across the different sequences. Good improvements were observed in preliminary experiments of pattern spoken term detection (STD) performed on both TIMIT and Mandarin Broadcast News with such enhanced patterns.
Variable structure control: a survey

A tutorial account of variable structure control with sliding mode is presented. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of this powerful control system design approach. This approach is particularly attractive for the control of nonlinear systems. Prominent characteristics such as invariance, robustness, order reduction, and control chattering are discussed in detail. Methods for coping with chattering are presented. Both linear and nonlinear systems are considered. Future research areas are suggested and an extensive list of references is included. >
Normalized CT dose index of the CT scanners used in the National Lung Screening Trial.

OBJECTIVE The National Lung Screening Trial includes 33 participating institutions that performed 75,133 lung cancer screening CT examinations for 26,724 subjects during 2002-2007. For trial quality assurance reasons, CT radiation dose measurement data were collected from all MDCT scanners used in the trial. MATERIALS AND METHODS A total of 247 measurements on 96 MDCT scanners were collected using a standard CT dose index (CTDI) measurement protocol. The scan parameters used in the measurements (tube voltage, milliampere-seconds [mAs], and detector-channel configuration) were set according to trial protocol for average size subjects. The normalized weighted CT dose index (CTDI(w)) (computed as CTDI(w)/mAs) obtained from each trial-participating scanner was tabulated. RESULTS We found a statistically significant difference in normalized CT dose index among CT scanner manufacturers, likely as a result of design differences, such as filtration, bow-tie design, and geometry. Our findings also indicated a statistically significant difference in normalized CT dose index among CT scanner models from the same manufacturer (e.g., GE Healthcare, Siemens Healthcare, and Philips Healthcare). We also found a statistically significant difference in normalized CT dose index among all models and all manufacturers; furthermore, we found a statistically significant difference in normalized CT dose index among CT scanners from all manufacturers when we compared scanners with four or eight data channels to those with 16, 32, or 64 channels, suggesting that more complex scanners have improved dose efficiency. CONCLUSION Average normalized CT dose index values varied by a factor of almost two for all scanners from all manufacturers. This study was focused on machine-specific normalized CT dose index; patient dose and image quality were not addressed.
In vivo molecular chemotherapy and noninvasive imaging with an infectivity-enhanced adenovirus.

BACKGROUND Adenovirus-based gene therapy is a promising approach to treat advanced cancers that are resistant to other treatments. However, many primary cells lack the requisite coxsackie-adenovirus receptor (CAR), limiting the in vivo efficacy of gene therapy. Recently, a modified adenovirus that is not dependent on CAR expression for infectivity was developed. We used noninvasive imaging to investigate the in vivo antitumor efficacy of gene therapy using this adenovirus in an animal model of ovarian cancer. METHODS The adenoviral vectors RGDTKSSTR (CAR-independent) and AdTKSSTR (CAR-dependent) express herpes simplex virus thymidine kinase (TK) for molecular chemotherapy and the human somatostatin receptor subtype 2 (SSTR) for noninvasive nuclear imaging. Subcutaneous or peritoneal human xenograft ovarian cancers were established from highly aggressive SKOV3.ip1 cells in immune-deficient mice. Adenoviral constructs were infected intratumorally or intraperitoneally once a day for 3 days. Control mice received three injections, one per day, of Ad5Luc1, a CAR-dependent adenoviral vector that includes a luciferase marker gene. The somatostatin analogue (99m)Tc-P2045 was used for noninvasive in vivo imaging of RGDTKSSTR that was injected into subcutaneous tumors. For mice with peritoneal tumors, survival was compared among the different treatment groups using Kaplan-Meier analysis with the log-rank statistic. All statistical tests were two-sided. RESULTS Tumor-associated RGDTKSSTR could be detected 15 days after introduction of the vector. In the subcutaneous model, tumors injected with RGDTKSSTR were statistically significantly smaller than those injected with AdTKSSTR (P<.001). In the intraperitoneal model, mice treated with RGDTKSSTR lived longer (survival at day 45 = 63.6%; 95% confidence interval [CI] = 35.2% to 92.0%) than those treated with AdTKSSTR (survival at day 45 = 0%) or Ad5Luc1 (survival at day 45 = 18.1%; 95% CI = 0.0% to 41.0%). DISCUSSION RGDTKSSTR shows antitumor efficacy against ovarian cancer in vivo in animal models. The virus can be imaged noninvasively and may have the potential to be a useful agent for treating ovarian cancer.
Prevalence of antibody to hepatitis C virus among Saudi Arabian children: A community‐based study

In a population‐based survey, 39 (0.90%) of 4,496 Saudi Arabian children (ages 1 to 10) were positive for antibody to hepatitis C virus. No significant difference was seen between the prevalence rate in males (0.9%) and females (0.8%) or between urban (0.7%) and rural dwellers (1.0%). A significant variation of rates (0% to 5.7%) was seen from one region to another. The Gizan population, noted for hyperendemic hepatitis B virus infection, had the highest prevalence of antibody to hepatitis C virus despite its cultural and socioeconomic similarities to other regions. In some regions of Saudi Arabia the prevalence of antibody to hepatitis C virus among children was 0% despite endemic rates for both hepatitis B virus and hepatitis A virus infections.
On Feasibility of Interference Alignment in MIMO Interference Networks

We explore the feasibility of interference alignment in signal vector space-based only on beamforming-for K-user MIMO interference channels. Our main contribution is to relate the feasibility issue to the problem of determining the solvability of a multivariate polynomial system which is considered extensively in algebraic geometry. It is well known, e.g., from Bezout's theorem, that generic polynomial systems are solvable if and only if the number of equations does not exceed the number of variables. Following this intuition, we classify signal space interference alignment problems as either proper or improper based on the number of equations and variables. Rigorous connections between feasible and proper systems are made through Bernshtein's theorem for the case where each transmitter uses only one beamforming vector. The multibeam case introduces dependencies among the coefficients of a polynomial system so that the system is no longer generic in the sense required by both theorems. In this case, we show that the connection between feasible and proper systems can be further strengthened (since the equivalency between feasible and proper systems does not always hold) by including standard information theoretic outer bounds in the feasibility analysis.
The use of machine translation tools for cross-lingual text mining

Eigen-analysis such as LSI or KCCA was already successfully applied to cross-lingual information retrieval. This approach has a weakness in that it needs an aligned training set of documents. In this paper we address this weakness and show that it can be successfully avoided through the use of machine translation. We show that the performance is similar on the domains where human generated training seta are available. However for other domains artiﬁcial training sets can be generated that signiﬁcantly outperform human generated ones obtained from a diﬀerent domain.
Genome analysis PSoL : a positive sample only learning algorithm for finding non-coding RNA genes

Motivation: Small non-coding RNA (ncRNA) genes play important regulatory roles in a variety of cellular processes. However, detection of ncRNA genes is a great challenge to both experimental and computational approaches. In this study, we describe a new approach called positive sample only learning (PSoL) to predict ncRNA genes in the Escherichia coli genome.AlthoughPSoL is amachine learningmethod for classification, it requires no negative training data,which, in general, is hard to define properly and affects the performanceofmachine learning dramatically. In addition, using thesupport vectormachine (SVM)as the core learning algorithm, PSoL can integrate many different kinds of information to improve the accuracy of prediction. Besides the application of PSoL for predicting ncRNAs, PSoL is applicable tomany other bioinformatics problems as well. Results: The PSoL method is assessed by 5-fold cross-validation experiments which show that PSoL can achieve about 80% accuracy in recovery of knownncRNAs.WecomparedPSoLpredictionswith five previously published results. The PSoL method has the highest percentage of predictions overlapping with those from other methods. Contact: srholbrook@lbl.gov Supplementary information: Supplementary data are available at Bioinformatics online.
Large-Scale Point-Cloud Visualization through Localized Textured Surface Reconstruction

In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets.
Mechanical vulnerability explains size-dependent mortality of reef corals

Understanding life history and demographic variation among species within communities is a central ecological goal. Mortality schedules are especially important in ecosystems where disturbance plays a major role in structuring communities, such as coral reefs. Here, we test whether a trait-based, mechanistic model of mechanical vulnerability in corals can explain mortality schedules. Specifically, we ask whether species that become increasingly vulnerable to hydrodynamic dislodgment as they grow have bathtub-shaped mortality curves, whereas species that remain mechanically stable have decreasing mortality rates with size, as predicted by classical life history theory for reef corals. We find that size-dependent mortality is highly consistent between species with the same growth form and that the shape of size-dependent mortality for each growth form can be explained by mechanical vulnerability. Our findings highlight the feasibility of predicting assemblage-scale mortality patterns on coral reefs with trait-based approaches.