Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoxic Culture Conditions as a Solution for Mesenchymal Stem Cell Based Regenerative Therapy

Cell-based regenerative therapies, based on in vitro propagation of stem cells, offer tremendous hope to many individuals suffering from degenerative diseases that were previously deemed untreatable. Due to the self-renewal capacity, multilineage potential, and immunosuppressive property, mesenchymal stem cells (MSCs) are considered as an attractive source of stem cells for regenerative therapies. However, poor growth kinetics, early senescence, and genetic instability during in vitro expansion and poor engraftment after transplantation are considered to be among the major disadvantages of MSC-based regenerative therapies. A number of complex inter- and intracellular interactive signaling systems control growth, multiplication, and differentiation of MSCs in their niche. Common laboratory conditions for stem cell culture involve ambient O2 concentration (20%) in contrast to their niche where they usually reside in 2–9% O2. Notably, O2 plays an important role in maintaining stem cell fate in terms of proliferation and differentiation, by regulating hypoxia-inducible factor-1 (HIF-1) mediated expression of different genes. This paper aims to describe and compare the role of normoxia (20% O2) and hypoxia (2–9% O2) on the biology of MSCs. Finally it is concluded that a hypoxic environment can greatly improve growth kinetics, genetic stability, and expression of chemokine receptors during in vitro expansion and eventually can increase efficiency of MSC-based regenerative therapies.
Improving Classification Accuracy of Decision Trees for Different Abstraction Levels of Data

Classification is an important problem in data mining. Given a database of records, each tagged with a class label, a classifier generates a concise and meaningful description for each class that can be used to classify subsequent records. Since the data is collected from disparate sources in many actual data mining environments, it is common to have data values in different abstraction levels. This article introduces the multiple abstraction level problem in decision tree classification, and proposes a method to deal with it. The proposed method adopts the notion of fuzzy relation for solving the multiple abstraction level problem. The experimental results show that the proposed method reduces classification error rates significantly when multiple abstraction levels of data are involved.
Molecular and biological characterization of the endogenous ecotropic provirus of BALB/c mice

We have isolated two identical molecular clones of the single, endogenous ecotropic provirus of BALB/c mice. The BALB/c clones are approximately 1/10 as infectious as an exogenous proviral clone derived from AKR mice, p623. Transfection of mouse cells with each BALB/c proviral clone yielded XC-negative, N-tropic, ecotropic virus. Cotransfection of subgenomic fragments of p623 and the BALB/c provirus did not increase infectivity to the level observed for p623; however, a 292-base-pair fragment of the p623 env gene was found to rescue XC-plaque formation. Sequence analysis showed that the XC-negative BALB/c provirus differed from the XC-positive AKR-derived provirus at a single nucleotide at the junction of the gp70 and p15E envelope proteins. Extensive sequence analysis of the BALB/c endogenous provirus showed that it differed from the sequence of the AKR-derived provirus at approximately 0.5% of 4,500 sequenced nucleotides. In addition, the BALB/c long terminal repeat contains a single copy of the enhancer-containing sequences that are repeated twice in p623. The limited variation between the ecotropic proviruses of BALB/c mice and AKR mice suggests that few cycles of reverse transcription separate these viral genomes.
Effects of preconditioning on myocardial regional contractility during low-flow ischaemia; the possible role of nitric oxide

Szigeti Zs, Simon K, Papp JGy, Parratt JR, Végh Á. Cardiac pacing reduces myocardial contractility during repeated low-flow ischaemia, 24 h later. J Mol Cell Cardiol 1999; 31: A97 Szigeti Zs, Simon K, Papp JGy, Végh Á. Repeated episodes of low-flow ischaemia decrease myocardial contractility in anaesthetized dogs. Cardiol Hung 1999; Suppl. 2: V.
Lighting Details Preserving Photon Density Estimation

Standard density estimation approaches suffer from visible bias due to low-pass filtering of the lighting function. Therefore, most photon density estimation methods have been used primarily with inefficient Monte Carlo final gathering to achieve high-quality results for the indirect illumination. We present a density estimation technique for efficiently computing all-frequency global illumination in diffuse and moderately glossy scenes. In particular, we compute the direct, indirect, and caustics illumination during photon tracing from the light sources. Since the high frequencies in the illumination often arise from visibility changes and surface normal variations, we consider a kernel that takes these factors into account. To efficiently detect visibility changes, we introduce a hierarchical voxel data structure of the scene geometry, which is generated on GPU. Further, we preserve the surface orientation by computing the density estimation in ray space.
Motion planning with interactive devices

This paper presents interaction between a user and a robot to guide motion through motion planning algorithm. The interaction aims at improving the guidance of an operator during a robot motion task in a virtual environment with the help of an automatic path planning algorithm. Existing works use a two-step decomposition which limits the interaction between the user and the ongoing process. We propose a modification of a classic motion planning method, the Rapidly-exploring Random Tree to build a Interactive-RRT. This method is based on exchanging forces between the algorithm and the user, and on data gathering (labels) from the virtual scene. Examples are shown to illustrate the Interactive motion planning system and analysis are done in function on the user's dexterity to manipulate devices.
The starvation hormone, fibroblast growth factor-21, extends lifespan in mice

Fibroblast growth factor-21 (FGF21) is a hormone secreted by the liver during fasting that elicits diverse aspects of the adaptive starvation response. Among its effects, FGF21 induces hepatic fatty acid oxidation and ketogenesis, increases insulin sensitivity, blocks somatic growth and causes bone loss. Here we show that transgenic overexpression of FGF21 markedly extends lifespan in mice without reducing food intake or affecting markers of NAD+ metabolism or AMP kinase and mTOR signaling. Transcriptomic analysis suggests that FGF21 acts primarily by blunting the growth hormone/insulin-like growth factor-1 signaling pathway in liver. These findings raise the possibility that FGF21 can be used to extend lifespan in other species. DOI: http://dx.doi. org/10.7554/eLife.00065. 001
Reusing Test-Cases on Different Levels of Abstraction in a Model Based Development Tool

Seamless model based development aims to use models during all phases of the development process of a system. During the development process in a component-based approach, components of a system are described at qualitatively differing abstraction levels: during requirements engineering component models are rather abstract high-level and underspeciﬁed, while during implementation the component models are rather concrete and fully speciﬁed in order to enable code generation. An important issue that arises is assuring that the concrete models correspond to abstract models. In this paper, we propose a method to assure that concrete models for system components reﬁne more abstract models for the same components. In particular we advocate a framework for reusing testcases at different abstraction levels. Our approach, even if it cannot completely prove the reﬁnement, can be used to ensure conﬁdence in the development process. In particular we are targeting the reﬁnement of requirements which are represented as very abstract models. Besides a formal model of our approach, we discuss our experiences with the development of an Adaptive Cruise Control (ACC) system in a model driven development process. This uses extensions which we implemented for our model-based development tool and which are brieﬂy presented in this paper.
Optimization for Statistical Machine Translation: A Survey

In statistical machine translation (SMT), the optimization of the system parameters to maximize translation accuracy is now a fundamental part of virtually all modern systems. In this article, we survey 12 years of research on optimization for SMT, from the seminal work on discriminative models (Och and Ney 2002) and minimum error rate training (Och 2003), to the most recent advances. Starting with a brief introduction to the fundamentals of SMT systems, we follow by covering a wide variety of optimization algorithms for use in both batch and online optimization. Specifically, we discuss losses based on direct error minimization, maximum likelihood, maximum margin, risk minimization, ranking, and more, along with the appropriate methods for minimizing these losses. We also cover recent topics, including large-scale optimization, nonlinear models, domain-dependent optimization, and the effect of MT evaluation measures or search on optimization. Finally, we discuss the current state of affairs in MT optimization, and point out some unresolved problems that will likely be the target of further research in optimization for MT.
Jezz: An effective legalization algorithm for minimum displacement

In this paper, we present a new method for circuit legalization called Jezz, which is, on average, 42.7% better than the classic legalization algorithm Tetris in terms of overall cell displacement, and 2.4% better than Abacus, a legalization algorithm that uses a quadratic function to compute the minimum cost for moving a cell, different from Jezz, that uses a linear function. The legalization step aligns cells to sites within the circuit rows and removes any overlapping among them while trying to minimize the total displacement of cells. Jezz can perform both full and incremental legalization, indicating the impact caused by inserting a cell in a row. It intrinsically handles cell-to-site alignment and has blockage support. A cache system is used to allow fast lookup during incremental legalization, allowing Jezz to support detailed placement algorithms. Although Jezz can be 20× slower than Tetris, the full legalization of a circuit with 200k cells takes less than a second, which makes Jezz suitable even for large scale designs, as a full legalization is run just a few times during the design flow.
Cardiovascular risk prediction: a comparative study of Framingham and quantum neural network based approach

Purpose Currently cardiovascular diseases (CVDs) are the main cause of death worldwide. Disease risk estimates can be used as prognostic information and support for treating CVDs. The commonly used Framingham risk score (FRS) for CVD prediction is outdated for the modern population, so FRS may not be accurate enough. In this paper, a novel CVD prediction system based on machine learning is proposed. Methods This study has been conducted with the data of 689 patients showing symptoms of CVD. Furthermore, the dataset of 5,209 CVD patients of the famous Framingham study has been used for validation purposes. Each patient’s parameters have been analyzed by physicians in order to make a diagnosis. The proposed system uses the quantum neural network for machine learning. This system learns and recognizes the pattern of CVD. The proposed system has been experimentally evaluated and compared with FRS. Results During testing, patients’ data in combination with the doctors’ diagnosis (predictions) are used for evaluation and validation. The proposed system achieved 98.57% accuracy in predicting the CVD risk. The CVD risk predictions by the proposed system, using the dataset of the Framingham study, confirmed the potential risk of death, deaths which actually occurred and had been recorded as due to myocardial infarction and coronary heart disease in the dataset of the Framingham study. The accuracy of the proposed system is significantly higher than FRS and other existing approaches. Conclusion The proposed system will serve as an excellent tool for a medical practitioner in predicting the risk of CVD. This system will be serving as an aid to medical practitioners for planning better medication and treatment strategies. An early diagnosis may be effectively made by using this system. An overall accuracy of 98.57% has been achieved in predicting the risk level. The accuracy is considerably higher compared to the other existing approaches. Thus, this system must be used instead of the well-known FRS.
Panoramic Video Techniques for Improving Presence in Virtual Environments

Photo-realistic techniques that use sequences of images captured from a real environment can be used to create virtual environments (VEs). Unlike 3D modelling techniques, the required human work and computation are independent of the amounts of detail and complexity that exist in the scene, and in addition they provide great visual realism. In this study we created virtual environments using three different photo-realistic techniques: panoramic video, regular video, and a slide show of panoramic still images. While panoramic video offered continuous movement and the ability to interactively change the view, it was the most expensive and time consuming to produce among the three techniques. To assess whether the extra effort needed to create panoramic video is warranted, we analysed how effectively each of these techniques supported a sense of presence in participants. We analysed participants' subjective sense of presence in the context of a navigation task where they travelled along a route in a VE and tried to learn the relative locations of the landmarks on the route. Participants' sense of presence was highest in the panoramic video condition. This suggests that the effort in creating panoramic video might be warranted whenever high presence is desired.
A New Order-Optimal Decentralized Coded Caching Scheme With Good Performance in the Finite File Size Regime

The decentralized coded caching scheme of Maddah-Ali and Niesen for the shared link network achieves an order-optimal memory-load tradeoff when the file size goes to infinity. It is then successively shown by Shanmugam et al. that, in the practical operating regime where the file size is finite, such a scheme yields a much less attractive coded caching gain. In this paper, we focus on designing decentralized coded caching schemes that can achieve low worst case loads of the shared link when the file size is finite and maintain order-optimal memory-load tradeoffs when the file size grows to infinity. First, we propose a decentralized coded caching design framework for designing decentralized coded caching schemes that can achieve significantly lower worst case loads than Maddah-Ali–Niesen’s decentralized coded caching scheme in the finite file size regime while maintaining order-optimal memory-load tradeoffs when the file size grows to infinity. Then, within the proposed framework, we propose a decentralized coded caching scheme, which is simple and tractable, and can achieve a low worst case load in both the finite and infinite file size regimes. We analyze the worst case load of the proposed scheme and show that it outperforms Maddah-Ali–Niesen’s and Shanmugam et al.’s decentralized schemes in the finite file size regime when the number of users is not too small. We also analyze the asymptotic worst case load of the proposed scheme when the file size goes to infinity and show that the proposed scheme achieves an order-optimal memory-load tradeoff. Finally, we analytically characterize the behavior of the worst case coded caching gain of the proposed scheme as a function of the required file size when the file size is large.
A new approach to video sequence recognition based on statistical methods

A fast method for image sequence recognition is presented. The method is based on a discrete statistical model consisting of a vector quantizer and a special probabilistic neural network, which allows one to classify image sequences without applying rules depending on the content of the sequence. The simple feature extraction also allows the classification with discrete hidden Markov models. As an application we present results from a test conducted for the classification of various gestures done by human beings in front of a video camera. For both classification methods we obtained promising recognition results in real time. The system obtained 90.0% recognition rate for person-independent classification of 10 or even 15 different gestures, which we considered as a surprisingly high rate for such a complex task. The system has been demonstrated at a large industrial fair and has confirmed its high recognition rates and its robustness under real-world conditions.
Test results from large wing and fuselage panels

This paper presents the first results in an assessment of the strength, stiffness, and damage tolerance of stiffened wing and fuselage subcomponents. Under this NASA funded program, 10 large wing and fuselage panels, variously fabricated by automated tow placement and dry-stitched preform/resin transfer molding, are to be tested. The first test of an automated tow placement six-longeron fuselage panel under shear load was completed successfully. Using NASTRAN finite-element analysis the stiffness of the panel in the linear range prior to buckling was predicted within 3.5 percent. A nonlinear analysis predicted the buckling load within 10 percent and final failure load within 6 percent. The first test of a resin transfer molding six-stringer wing panel under compression was also completed. The panel failed unexpectedly in buckling because of inadequate supporting structure. The average strain was 0.43 percent with a line load of 20.3 kips per inch of width. This strain still exceeds the design allowable strains. Also, the stringers did not debond before failure, which is in contrast to the general behavior of unstitched panels.
Nucleotide interconversions. IV. Activities of deoxycytidylate deaminase and thymidylate synthetase in normal rat liver and hepatomas.

Normal and neoplastic rat liver was analyzed for deoxycytidylate deaminase and thymidylate synthetase. For these assays, highly sensitive radiochemical methods capable of detecting the formation of less than 0.001 µ mole of deoxyuridylate and thymidylate were employed. Deoxycytidylate deaminase was found in normal adult rat liver, rat embryo liver, regenerating liver, Novikoff hepatoma, Dunning hepatoma, and the Morris 5123 hepatoma, sublines A, B, and C. The deaminase varied in activity from a low of 2 µ moles of deoxyuridylate formed/gm protein/hour for adult rat liver to a high of 750 µ moles formed /gm protein/hour for the Novikoff hepatoma. The results suggest the possibility of a correlation between growth rate and deaminase activity. Thymidylate synthetase was less variable in activity, ranging from 2 to 12 µ moles of thymidylate formed/gm protein/hour. This enzyme was measurable in all the tissues studied except in normal adult rat liver. Analysis of the compounds obtained by conducting the deaminase assay in the presence and absence of fluoride revealed interesting differences in the tissues mentioned above. The apparent enhanced deoxycytidylate deaminase activity in extracts of the Novikoff, Dunning, and Morris 5123 (subline B) hepatomas, incubated in the absence of fluoride, was due to a nucleoside deaminase. This activity could not be detected with deoxycytidine-2-C14 as substrate in extracts of the other tissues. The apparent phosphatase activity in regenerating liver and rat embryo liver extracts, as determined from ion-exchange elution patterns, was appreciably lower than that in normal adult rat liver and the various neoplasms studied. These results have been confirmed by measuring phosphate release from various deoxynucleoside 5′-phosphates.
On CFI and CFI-based filters

We have proposed that the co-occurrence frequency image based on the co-occurrence frequency histogram of the gray value of an image has a new potential to introduce a new scheme for image feature extraction. This paper proposes a couple of new enhancement filters to achieve sharpening and smoothing of images. These filters are very similar to but quite different from those which have been used so far. Thus, we could show a possibility for introducing a new paradigm for basic image enhancement filters. We also introduce the application for wrinkle extraction from facial image.
Satellites of the Largest Kuiper Belt Objects

We have searched the four brightest objects in the Kuiper Belt for the presence of satellites using the newly commissioned Keck Observatory Laser Guide Star Adaptive Optics system. Satellites are seen around three of the four objects: Pluto (whose satellite Charon is well-known and whose recently discovered smaller satellites are too faint to be detected), 2003 EL61 (where a second satellite is seen in addition to the previously known satellite), and 2003 UB313 (where a satellite is seen for the first time). The object 2005 FY9, the brightest Kuiper Belt object (KBO) after Pluto, does not have a satellite detectable within 0. ″4 with a brightness of more than 1% of the primary. The presence of satellites around three of the four brightest KBOs is inconsistent with the fraction of satellites in the Kuiper Belt at large at the 99.2% confidence level, suggesting a different formation mechanism for these largest KBO satellites. The two satellites of 2003 EL61, and the one satellite of 2003 UB313, with fractional brightnesses of 5% and 1.5%, and 2%, of their primaries, respectively, are significantly fainter relative to their primaries than other known KBO satellites, again pointing to possible differences in their origin.
Joint effect among p53, CYP1A1, GSTM1 polymorphism combinations and smoking on prostate cancer risk: an exploratory genotype-environment interaction study.

AIM To assess the role of several genetic factors in combination with an environmental factor as modulators of prostate cancer risk. We focus on allele variants of low-penetrance genes associated with cell control, the detoxification processes and smoking. METHODS In a case-control study we compared people carrying p53cd72 Pro allele, CYP1A1 M1 allele and GSTM1 null genotypes with their prostate cancer risk. RESULTS The joint risk for smokers carrying Pro* and M1*, Pro* and GSTM1null or GSTM1 null and CYP1A1 M1* variants was significantly higher (odds ratio [OR]: 13.13, 95% confidence interval [CI]: 2.41-71.36; OR: 3.97, 95% CI: 1.13-13.95 and OR: 6.87, 95% CI: 1.68-27.97, respectively) compared with that for the reference group, and for non-smokers was not significant. OR for combinations among p53cd72, GSTM1 and CYP1A1 M1 in smokers were positively and significantly associated with prostate cancer risk compared with non-smokers and compared with the putative lowest risk group (OR: 8.87, 95% CI: 1.25-62.71). CONCLUSION Our results suggest that a combination of p53cd72, CYP1A1, GSTM1 alleles and smoking plays a significant role in modified prostate cancer risk on the study population, which means that smokers carrying susceptible genotypes might have a significantly higher risk than those carrying non-susceptible genotypes.