Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditional Knockout of Telomerase Reverse Transcriptase in Mesenchymal Cells Impairs Mouse Pulmonary Fibrosis

Telomerase is typically expressed in cellular populations capable of extended replication, such as germ cells, tumor cells, and stem cells, but is also induced in tissue injury, repair and fibrosis. Its catalytic component, telomerase reverse transcriptase (TERT) is induced in lung fibroblasts from patients with fibrotic interstitial lung disease and in rodents with bleomycin-induced pulmonary fibrosis. To evaluate the fibroblast specific role of TERT in pulmonary fibrosis, transgenic mice bearing a floxed TERT allele were generated, and then crossed with an inducible collagen α2(I)-Cre mouse line to generate fibroblast specific TERT conditional knockout mice. TERT-specific deficiency in mesenchymal cells caused attenuation of pulmonary fibrosis as manifested by reduced lung hydroxyproline content, type I collagen and α-smooth muscle actin mRNA levels. The TERT-deficient mouse lung fibroblasts displayed decreased cell proliferative capacity and higher susceptibility to induced apoptosis compared with control cells. Additionally TERT deficiency was associated with heightened α-smooth muscle actin expression indicative of myofibroblast differentiation. However the impairment of cell proliferation and increased susceptibility to apoptosis would cause a reduction in the myofibroblast progenitor population necessary to mount a successful myofibroblast-dependent fibrotic response. These findings identified a key role for TERT in fibroblast proliferation and survival essential for pulmonary fibrosis.
Formal concept analysis in relational contexts

Formal concept analysis (FCA) is a method mainly used for the analysis of data, which identifies conceptual structures among data sets. Central to FCA is the notion of formal context. A formal context is usually defined as a binary relation between a set of objects and a set of attributes. But in real world, it is more meaningful to consider the direct relations between objects (or individuals). In this paper, in order to model those relations between individuals in real world, we shall propose a different kind of context - relational context for FCA, which contains a universe U of objects and a binary relation r on U. The definitions of relational concepts in relational contexts and the basic properties about relational contexts and relational concepts are also given.
Chemical Graphs: Looking Back and Glimpsing Ahead

Graph-theoretical applications to chemistry are reviewed from a personal point of view in the context of the gradual acceptance of the value of such applications by the chemical and informational community. Initial problems involved enumerations of isomers that required the use of molecular (constitutional) graphs and techniques such as Polya’s theorem, including valence isomers of annulenes, benzenoids, and diamond hydrocarbons (polymantanes). Problems connected with structural coding and retrieval of chemical information followed. Reaction graphs exemplify a different type of graphs. For QSAWQSPR studies, global graph invariants (topological indices, TIS) have proved their usefulness; they are based on local vertex invariants (LOVIs) which until recently were exclusively integers, leading to high degeneracy of TIS. Newly introduced real-number LOVIs are briefly reviewed. This retrospective section ends with applications of graph theory (GT) to elemental carbon nets and to fullerenes. Then a few predictions are made for promising developments in the future: increasing use of GT for information processing, development of LOVIs and TIS incorporating stereochemical features, and increased use of TIS for molecular modeling and drug design, along with more sophisticated molecular graphics methods.
Non-intuitive conditional independence facts hold in models of network data

Many social scientists and researchers across a wide range of fields focus on analyzing a single causal dependency or a conditional model of some outcome variable. However, to reason about interventions or conditional independence, it is useful to construct a joint model of a domain. Researchers in computer science, statistics, and philosophy have developed representations (e.g., Bayesian networks), theory, and learning algorithms for causal discovery of joint models from observational data. Bayesian networks are graphical models that encode joint probability distributions over a system of variables, and they can be interpreted causally under a few assumptions [7, 8]. The rules of d-separation—a set of graphical criteria—are the foundation for algorithmic derivation of the conditional independence facts implied by the structure of Bayesian networks [1]. This theory connects causal structure with conditional independence and can be leveraged to learn causal models from observational data. Accurate reasoning about conditional independence facts is the basis for constraintbased algorithms that learn the structure of Bayesian networks (e.g., PC [8]). Bayesian networks, as well as most analytic methods for causal analysis (e.g., linear regression), assume that data instances are independent and identically distributed (IID). However, many real-world systems involve multiple types of interacting entities with probabilistic dependencies among the variables on those entities. For example, citation data involve researchers collaborating on scholarly papers that cite prior work. Over the past 15 years, researchers in statistics and computer science have devised more expressive classes of directed graphical models, such as probabilistic relational models (PRMs), which remove the assumptions of IID data to model network, or relational, data [2]. Relational models more closely represent the real-world domains that many social scientists and other researchers investigate. To successfully learn causal models from observational, network data, we need a similar theory for deriving conditional independence from relational models. In this paper, we explain why d-separation does not correctly produce conditional independence facts when applied to the structure of relational models. We show that nonintuitive conditional independence facts hold in models of network data through relationally d-connecting paths that only manifest in ground graphs. We describe the abstract ground graph, a lifted representation recently introduced by Maier et al. [4], that enables a sound, complete, and computationally efficient method for deriving conditional independ-separating path elements (exists one on path) d-connecting path elements (exists all on path)
Bio-cooperative robotics: Controlling mechanical, physiological and mental patient states

In classical man-machine interfaces, biomechanics of the human form a part of the underlying control loop. However, integrating the human into the loop can be considered not only from a biomechanical view but also with regard to psycho-physiological aspects. Biomechanical integration involves ensuring that the system to be used is ergonomically acceptable and “user-cooperative”. Psycho-physiological integration involves recording and controlling the patient's physiological reactions so that the patient receives appropriate stimuli and is challenged in a moderate but engaging way without causing undue stress or harm. In this paper, we present examples of biomechanical and psycho-physiological integration of patients verified with the gait robot Lokomat and the dynamic tilt and stepping device Erigo.
Receiver- and Channel-adaptive Compression for Remote Browsing of Image- Based Scene Representations

Remote navigation in compressed imagebased scene representations requires random access to arbitrary parts of the reference image data to recompose virtual views. The degree of inter-frame dependencies exploited during compression has an impact on the effort needed to access reference images and delimits the rate distortion (RD) trade-off that can be achieved. This work considers conventional RD optimization but additionally takes a given receiver hardware and a maximum available transmission bitrate into account. This leads to an extension of the traditional ratedistortion optimization to a trade-off between the four parameters rate (server side file size), distortion, transmission data rate, and decoding complexity. This RDTC optimization framework allows us to adapt to channel properties and client resources and can significantly improve the user satisfaction in a remote navigation scenario. Index Terms – IBR streaming, adaptive compression, RD optimization
Research on Network Traffic Forecasting Strategy Based on BP Neural Network

resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on BP neural network, then modeling and forecasting the time series of network traffic data; Second, we construct three module, namely, data collection, data processing and traffic forecasting; Last, we use the strong memory and the learning ability of BP neural network to shortterm forecast the network traffic . This model can provide a basis for network monitoring and management and has high application value and very wide meaning.
Mycophenolate mofetil in the treatment of lupus nephritis

Lupus nephritis is a complication of systemic lupus erythematosus, which has significant morbidity and mortality. The accepted standard of treatment for severe lupus nephritis is cyclophosphamide for induction of remission. This has significant adverse effects including severe infection and amenorrhea. In addition, although cyclophosphamide induces remission, long-term mortality does not seem to be altered. Mycophenolate mofetil (MMF) is an immunosuppressive agent originally used in solid organ transplantation, which has been compared with cyclophosphamide in trials for lupus nephritis. Randomized trials with MMF have been relatively small, although pooled data seem to suggest that it is at least as effective as cyclophosphamide in inducing remission. In addition, MMF has also been associated with a reduced risk of infection and amenorrhea, although this finding is not universal. MMF appears to be associated with more diarrhea compared with cyclophosphamide. MMF is likely to be a useful treatment for lupus nephritis, although available trial data are limited due to the small size of previous studies. A large trial (the Aspreva Lupus Management Study) is currently underway to attempt to establish the place of MMF in treatment of lupus nephritis.
Image Retrieval Based on Anisotropic Scaling and Shearing Invariant Geometric Coherence

Imposing a spatial coherence constraint on image matching is becoming a necessity for local feature based object retrieval. We tackle the affine invariance problem of the prior spatial coherence model and propose a novel approach for geometrically stable image retrieval. Compared with related studies focusing simply on translation, rotation, and isotropic scaling, our approach can deal with more significant transformations including anisotropic scaling and shearing. Our contribution consists of revisiting the first-order affine adaptation approach and extending its application to represent the geometric coherence of a second-order local feature structure. We comprehensively evaluated our approach using Flickr Logos 32, Holiday, and Oxford Buildings benchmarks. Extensive experimentation and comparisons with state-of-the-art spatial coherence models demonstrate the superiority of our approach in image retrieval tasks.
Power-Aware Compilation with Architectural Support and Instruction Scheduling

This paper is to develop an innovative technique using dynamic voltage scaling (DVS) to reduce the energy dissipation. The objective of our work is to maximize the period of idle functional units and minimize the transitions between power modes. To achieve this goal, our work is performed in the following steps. First, the program will be built as a control flow graph that comprises many regions. Second, we build the power model of the program and collect the power information by profiling the control flow graph. Then the regions with the same functional units will be merged if the merging still preserves the program dependencies. Next, the idle functional units will be turned off and each region will be assigned a power mode based on the power model. Finally, the program is rescheduled to merge the regions to reduce the transitions between power modes. Our work is implemented on the basis of SUIF2 compiler infrastructure and the Wattach simulator and measured by using SPEC2000, DSPstone, and JPEG decoder as benchmarks. On average, the experimental results show that our work can save the energy by 26% with performance degradation between 5% and 18%.
The Effects of 8 Weeks of Vitamin C Intake and Regular Aerobic Exercise on Serum Brain-Derived Neurotrophic Factor and Insulin-like Growth Factor-1 Levels in Obese Girls

شور و داوم اه : ،یبرجت همین قیقحت نیا رد 28 نیماتیو ،نیرمت ،لرتنک هورگ راهچ هب یفداصت روط هب و باختنا قاچ رتخد C یبیکرت و دندش میسقت . نیرمت تدش اب يزاوه 50 ات 70 ،رثکادح بلق نابرض دصرد 3 تدم هب و هتفه رد هسلج 8 هتفه دش ماجنا . هورگ ياه نیماتیو C و صرق یبیکرت 500 یلیم نیماتیو یمرگ C ار 3 فرصم هتفه رد راب دندومن . هنومن و لبق اتشان ینوخ ياه 48 هلخادم نیرخآ زا سپ تعاس اه عمج دش يروآ . یمرس حوطس BDNF و IGF-1 هب شور اب بیترت ياه هزادنا یساونمیا میزنآ و ازیلاا دش يریگ .
What Knowledge about Handwritten Letters can be Used to Recover their Drawing Order

A way to do off-line handwriting recognition is to generate an equivalent on-line signal of a letter image and to use an on-line recognition system to recognize this letter. To do this, the drawing order has to be recovered using handwriting knowledge. Our approach to recover the drawing order consists in proposing several starting and ending points. Several paths are generated and the best one is chosen. This paper presents the handwriting knowledge introduced at several steps of our method and its contribution for the recognition process. Experimentations have been carried out on isolated lower case multistroke letters from a database including both on-line and off-line signals. An on-line system has been used to recognize these letters.
The 9-Hole Peg Test of Upper Extremity Function: Average Values, Test-Retest Reliability, and Factors Contributing to Performance in People With Parkinson Disease

Background and Purpose: Pegboard tests of hand dexterity are commonly used in clinical settings to assess upper extremity function in various populations. For individuals with Parkinson disease (PD), the clinical utility of pegboard tests has not been fully evaluated. Our purpose was to examine the commercially available 9-Hole Peg Test (9HPT) using a large sample of individuals with PD to determine average values, test-retest reliability, and factors predictive of 9HPT performance. Methods: A total of 262 participants with PD (67% men, Hoehn & Yahr stage = 2.3 ± 0.7) completed the 9HPT along with a battery of other tests including the Movement Disorder Society Unified PD Rating Scale—Motor Subscale III and Freezing of Gait Questionnaire. Results: Average time to complete the 9HPT was 31.4 ± 15.7 s with the dominant and 32.2 ± 12.4 s with the nondominant hand. Test-retest reliability of 2 trials performed with the same hand was high (dominant ICC2,1 = 0.88, nondominant ICC2,1 = 0.91). Women performed the test significantly faster than men, and nonfreezers significantly faster than freezers. For either hand, age, bradykinesia, and freezing of gait scores individually predicted significant portions of the variance in 9HPT time. Sex also was a significant predictor, but for the nondominant hand only. Tremor and rigidity did not predict performance. Discussion and Conclusions: The 9HPT appears to be a clinically useful measure for assessing upper extremity function in individuals with PD. The 9HPT has advantages over previously used methods including standardization, known normative values for healthy controls, commercial availability, transportability, and ease of administration.
A comparative experimental analysis of separate and combined facial features for GA-ANN based technique

This paper investigates a feature selection and classification technique for face recognition using genetic algorithms and artificial neural networks. The experiments using separate facial features and combined facial features have been conducted on a face image dataset which is extracted from FERET benchmark database and was used in our previous study. The experiments using just combined features have also been conducted on an extended version of this dataset. The new experiments have achieved much better recognition rate than some of the existing face recognition techniques and significantly improved our previously published results. A detailed comparative analysis of experimental results is included in this paper.
Agricultural exposures and cancer trends in developed countries.

Recent increases have been reported in industrial countries for several sites of cancer. The causes of these increases remain unknown. Efforts should proceed to identify those occupational groups with increases in the same sites, as these may indicate relevant exposures. Two analyses were undertaken: trends in cancer mortality in industrial countries were reviewed to identify recently increasing sites and summaries were compiled of studies on farmers which have shown increased risks for these same sites of cancer. Using data provided by the World Health Organization, age-specific rates were developed for a number of sites of cancer from 1968 to 1986. Trends in the ratio of male to female cancer mortality were also assessed for several of these countries. Based on a literature review by the National Cancer Institute, patterns of cancer in farmers reported in 20 studies from 8 countries are summarized, weighting each study by its size to create combined relative risks. In industrial countries, rates of cancer mortality increased for a number of sites, including melanoma, prostate, non-Hodgkin's lymphoma, multiple myeloma, breast, brain, and kidney cancer. The ratio of male to female cancer mortality (for all sites of cancer excluding lung) has generally increased in several countries during this same time period. Many of the same sites that have increased in the general population have also been found to be increasing in farmers. Significant excesses occurred for Hodgkin's disease, multiple myeloma, leukemia, skin melanomas, and cancers of the lip, stomach, and prostate. Nonsignificant increases in risk were also noted for non-Hodgkin's lymphoma and cancers of connective tissue and brain in many surveys. (ABSTRACT TRUNCATED AT 250 WORDS)
Multiplicative Approximation of Wealth Processes Involving No-Short-Sale Strategies

A financial market model with general semimartingale asset-price processes and where agents can only trade using no-short-sale strategies is considered. We show that wealth processes using continuous trading can be approximated very closely by wealth processes using simple combinations of buy-and-hold trading. This approximation is based on controlling the proportions of wealth invested in the assets. As an application, the utility maximization problem is considered and it is shown that optimal utilities and wealth processes resulting from continuous trading can be approximated arbitrarily well by the use of simple combinations of buy-and-hold strategies.
Lossless hyperspectral image compression based on prediction

Hyperspectral imaging technology plays an important role in the field of remote sensing applications. Hyperspectral images exhibit significant spectral correlation whose exploitation is crucial for compression. In this paper an efficient method for Hyperspectral image compression is presented based on differential prediction with very low complexity. The proposed scheme consists of a difference coder, two predictors and a Huffman codec. The processing of the pixels varies depending on their position in the image. The resulting difference between the predicted and the actual pixel values are encoded into variable-length codewords using the Huffman codebook. The performance of the proposed algorithm has been evaluated on AVIRIS images. The experimental results show that with a Compression Ratio (CR) up to 4.14, the proposed method provides a competitive performance with comparison of JPEG2000, JPEG-LS and the OCC schemes.
CONSISTENT PARAMETER ESTIMATION FOR CORRUPTED MARKOV RANDOM FIELDS : WITH APPLICATIONS TO IlVlAGE ANALYSIS

The parameter estimation problem for regression models with errors in variables is considered for the spatial Markov random fields models. Consistency of the estimates is proved in various examples of both categorical and continuos signals. When using the most common procedures of image restoration, such as the iterative conditional modes algorithm or the annealing algorithm, the res~lts relies heavily on choice of parameters that in practise need to beestiIIIated,developingconsistentestimation procedures. is thus of importance to the'fiefdof image restoration. The estimation problem is considered in a variety of different examples, and consistent estimates are derived for the signal process, when parameters for the noise process are fixed and known. American Society 1970 subject classmcanon, Primary 60G35, 60G60, 62FIO; Secondary 60K35, 62K99, 62M30.
Application of hierarchical modeling concepts to a multi-analysis environment

An environment which enables the application of multiple analysis formalisms or paradigms to a commonly defined problem is extended to include hierarchical modeling concepts. A description of the development of the object-oriented environment is provided as background. Concepts of model development are introduced in order to emphasize the value of hierarchical modeling concepts. Implementation of these concepts in the environment is then discussed. The implementation of experimental frame concepts, in which system behavior represented in the model is separated from behavior related to experimentation, is explored. Hierarchical concepts are then applied to the pairing of a model with an experimental frame in order to address future simulation goals such as hybrid and multilevel simulation. <<ETX>>
Efficient Management of Spatial RDF Data

The RDF data model has recently been extended to support representation and querying of spatial information (i.e., locations and geometries), which is associated with RDF entities. Still, there are limited efforts towards extending RDF stores to efficiently support spatial queries, such as range selections (e.g., find entities within a given range) and spatial joins (e.g., find pairs of entities whose locations are close to each other). In this paper, we propose an extension for RDF stores that supports efficient spatial data management. Our contributions include an effective encoding scheme for entities having spatial locations, the introduction of on-the-fly spatial filters and spatial join algorithms, and several optimizations that minimize the overhead of geometry and dictionary accesses. We implemented the proposed techniques as an extension to the open-source RDF-3X engine and we experimentally evaluated them using real RDF knowledge bases. The results show that our system offers robust performance for spatial queries, while introducing little overhead to the original query engine.