Miracle-dz/UniFAR-FTUs huggingface dataset:
On the equilibrium morphology of systems drawn from spherical collapse experiments

We present a purely theoretical study of the morphological evolution of self-gravitating systems formed through the dissipationless collapse of N-point sources. We explore the effects of resolution in mass and length on the growth of triaxial structures formed by an instability triggered by an excess of radial orbits. We point out that as resolution increases, the equilibria shift, from mildly prolate, to oblate. A number of particles N ≃ 100000 or larger is required for convergence of axial aspect ratios. An upper bound for the softening, ∈ ≈ 1/256, is also identified. We then study the properties of a set of equilibria formed from scale-free cold initial mass distributions, ρ α r -γ ; 0 ≤ γ ≤ 2. Oblateness is enhanced for initially more peaked structures (larger values of y). We map the run of density in space and find no evidence for a power-law inner structure when γ ≤ 3/2 down to a mass fraction ≤0.1 per cent of the total. However, when 3/2 < γ ≤ 2, the mass profile in equilibrium is well matched by a power law of index ≈ γ out to a mass fraction % 10 per cent. We interpret this in terms of less-effective violent relaxation for more peaked profiles when more phase mixing takes place at the centre. We map out the velocity field of the equilibria and note that at small radii the velocity coarse-grained distribution function (DF) is Maxwellian to a very good approximation. We extend our study to non-scale-free initial conditions and finite but subvirial kinetic energy. For cold collapses, the equilibria are again oblate, as the scale-free models. With increasing kinetic energy, the equilibria first shift to prolate morphology and then to spherical symmetry.
Personalized Video Recommendation through Graph Propagation

The rapid growth of the number of videos on the Internet provides enormous potential for users to find content of interest. However, the vast quantity of videos also turns the finding process into a difficult task. In this article, we address the problem of providing personalized video recommendation for users. Rather than only exploring the user-video bipartite graph that is formulated using click information, we first combine the clicks and queries information to build a tripartite graph. In the tripartite graph, the query nodes act as bridges to connect user nodes and video nodes. Then, to further enrich the connections between users and videos, three subgraphs between the same kinds of nodes are added to the tripartite graph by exploring content-based information (video tags and textual queries). We propose an iterative propagation algorithm over the enhanced graph to compute the preference information of each user. Experiments conducted on a dataset with 1,369 users, 8,765 queries, and 17,712 videos collected from a commercial video search engine demonstrate the effectiveness of the proposed method.
Fully Secure Hidden Ciphertext Policy Attribute-Based Encryption with Short Ciphertext Size

In ciphertext policy attribute-based encryption scheme, access policies are associated with ciphertext and tied to it. It is necessary to hide the access policy in the most sensitive spots such as political, medical and economic fields, that is, receiver's anonymity. In this paper, we propose an efficient CP-ABE construction with hidden policy and prove it to be fully secure under static assumptions applying the dual system encryption methodology. Access structures in our construction are AND gates on positive, negative and wildcard attributes and the ciphertext size is short, which is only concerned with the number of wildcards.
Specific Intensity Direct Current (DC) Electric Field Improves Neural Stem Cell Migration and Enhances Differentiation towards βIII-Tubulin+ Neurons

Control of stem cell migration and differentiation is vital for efficient stem cell therapy. Literature reporting electric field–guided migration and differentiation is emerging. However, it is unknown if a field that causes cell migration is also capable of guiding cell differentiation—and the mechanisms for these processes remain unclear. Here, we report that a 115 V/m direct current (DC) electric field can induce directional migration of neural precursor cells (NPCs). Whole cell patching revealed that the cell membrane depolarized in the electric field, and buffering of extracellular calcium via EGTA prevented cell migration under these conditions. Immunocytochemical staining indicated that the same electric intensity could also be used to enhance differentiation and increase the percentage of cell differentiation into neurons, but not astrocytes and oligodendrocytes. The results indicate that DC electric field of this specific intensity is capable of promoting cell directional migration and orchestrating functional differentiation, suggestively mediated by calcium influx during DC field exposure.
Neuroprotective Effects of Growth Hormone Against Hypoxic-Ischemic Brain Injury in Neonatal Rats: 1H Magnetic Resonance Spectroscopic Study

Using 1H-MRS, we evaluated the effects of growth hormone (GH) as a caspase inhibitor on hypoxic-ischemic injury in neonatal rat brains. The right common carotid arteries of rats were ligated, allowed to recover for 3 hr, and exposed to 8% oxygen for 2 hr. GH was given just prior to HI insult and animals were divided into four groups: control, intracerebroventricular (ICV), intracerebroventricular/intraperitoneal (ICV/IP), and intraperitoneal (IP). Localized in vivo 1H-MRS and TUNEL staining were performed 24 hr after HI injury. Lipid/N-acetyl aspartate (NAA) and lipid/creatine (Cr) ratios were used as apoptotic markers. Gross morphologic changes at 2 weeks were used to evaluate the effects of GH. The lipid/NAA ratio was lower in the ICV and ICV/IP groups than in the control, and the lipid/Cr ratio was lower in the ICV group than in the control. The number of TUNEL positive cells was decreased in the ICV and ICV/IP groups, and the degree of morphologic change indicative of brain injury was lower in the ICV group and somewhat lower in the ICV/IP group. The degree of morphologic change correlated with the lipid/NAA and lipid/Cr ratios. These findings suggest that GH exerts neuroprotective effects in cerebral hypoxic-ischemic injury.
Impact of the New Generation Reconstituted Surfactant CHF5633 on Human CD4+ Lymphocytes

Background Natural surfactant preparations, commonly isolated from porcine or bovine lungs, are used to treat respiratory distress syndrome in preterm infants. Besides biophysical effectiveness, several studies have documented additional immunomodulatory properties. Within the near future, synthetic surfactant preparations may be a promising alternative. CHF5633 is a new generation reconstituted synthetic surfactant preparation with defined composition, containing dipalmitoyl-phosphatidylcholine, palmitoyl-oleoyl-phosphatidylglycerol and synthetic analogs of surfactant protein (SP-) B and SP-C. While its biophysical effectiveness has been demonstrated in vitro and in vivo, possible immunomodulatory abilities are currently unknown. Aim The aim of the current study was to define a potential impact of CHF5633 and its single components on pro- and anti-inflammatory cytokine responses in human CD4+ lymphocytes. Methods Purified human CD4+ T cells were activated using anti CD3/CD28 antibodies and exposed to CHF5633, its components, or to the well-known animal-derived surfactant Poractant alfa (Curosurf®). Proliferative response and cell viability were assessed using flow cytometry and a methylthiazolyldiphenyltetrazolium bromide colorimetric assay. The mRNA expression of IFNγ, IL-2, IL-17A, IL-22, IL-4, and IL-10 was measured by quantitative PCR, while intracellular protein expression was assessed by means of flow cytometry. Results Neither CHF5633 nor any of its phospholipid components with or without SP-B or SP-C analogs had any influence on proliferative ability and viability of CD4+ lymphocytes under the given conditions. IFNγ, IL-2, IL-17A, IL-22, IL-4, and IL-10 mRNA as well as IFNγ, IL-2, IL-4 and IL-10 protein levels were unaffected in both non-activated and activated CD4+ lymphocytes after exposure to CHF5633 or its constituents compared to non-exposed controls. However, in comparison to Curosurf®, expression levels of anti-inflammatory IL-4 and IL-10 mRNA were significantly increased in CHF5633 exposed CD4+ lymphocytes. Conclusion For the first time, the immunomodulatory capacity of CHF5633 on CD4+ lymphocytes was evaluated. CHF5633 did not show any cytotoxicity on CD4+ cells. Moreover, our in vitro data indicate that CHF5633 does not exert unintended pro-inflammatory effects on non-activated and activated CD4+ T cells. As far as anti-inflammatory cytokines are concerned, it might lack an overall reductive ability in comparison to animal-derived surfactants, potentially leaving pro- and anti-inflammatory cytokine response in balance.
Collaborative framework for browser games development

In this paper we do a review of research in software and game development, game modding communities, open-source development and open content creation. The ideas gathered in this research used to create a conceptual model for the creation of a collaborative on-line framework for browser games development. The generated conceptual model will be used in future work to build and test the framework.
High ponderal index at birth predicts high estradiol levels in adult women

Inter‐individual variation in levels of sex hormones results from differences in genetic, developmental, and environmental factors. We tested a hypothesis that programming of the fetal neuroendocrine axis may predispose some women to produce higher levels of steroid hormones during their menstrual cycles as adults. One hundred forty‐five regularly menstruating 24‐ to 36‐ year‐old women collected daily saliva samples for one menstrual cycle. Data on women's birth weights and birth lengths were obtained from medical records. A positive relationship was observed between ponderal index at birth (an indicator of nutritional status, calculated as birth weight/(birth length)3) and levels of estradiol (E2) in menstrual cycles, after controlling for potential confounding factors. Mean E2 was 16.4 pmol/l in the low ponderal index tertile, 17.3 pmol/l in the moderate ponderal index tertile, and 19.6 pmol/l in the high ponderal index tertile (the high ponderal index group had significantly higher E2 than both low and moderate ponderal index groups, P = 0.0001). This study shows a positive association between ponderal index recorded for women at birth and levels of E2 measured during their menstrual cycles as adults. This suggests that conditions during fetal life influence adult production of reproductive hormones and may contribute to inter‐individual variation in reproductive function. In addition, because large size at birth is one of the factors linked with an increased risk of breast cancer, our findings provide a physiological link for the observed positive relationship between indicators of energetic conditions during fetal growth and breast cancer in women. Am. J. Hum. Biol. 18:133–140, 2006. © 2005 Wiley‐Liss, Inc.
Automatic WCET Reduction by Machine Learning Based Heuristics for Function Inlining

The application of machine learning techniques in compiler frame- works has become a challenging research area. Learning algorithms are exploited for an automatic generation of optimization heuristics which often outperform hand-crafted models. Moreover, these automatic approaches can effectively tune the compilers' heuristics after larger changes in the optim ization sequence or they can be leveraged to tailor heuristics towards a particular a rchitectural model. Pre- vious works focussed on a reduction of the average-case performance. In this paper, learning approaches are studied in the context of an automatic min- imization of the worst-case execution time (WCET) which is the upper bound of the program's maximum execution time. We show that explicitly taking the new timing model into account allows the construction of compiler heuristics that effectively reduce the WCET. This is demonstrated for the well-known opti- mization function inlining. Our WCET-driven inlining heuristics based on a fast classifier called random forests outperform standard heuristics by up to 9.1% on average in terms of the WCET reduction. Moreover, we point out that our classi- fier is highly accurate with a prediction rate for inlining ca ndidates of 84.0%.
Experimental Power Analysis Attacks on an FPGA

Power analysis attacks is becoming an increasingly more researched field in cryptography. This paper summarizes the study of S.B. Ors, E. Oswald, and B. Preneel on power attacks using FPGAs. FPGAs are widely used because of their flexibility and relative ease of use. They are not only used in lab environments for prototyping, but also in production environments which makes them good experimental devices. Their study was completed on a Xilinx Virtex 800 FPGA. Their analysis was done using an implementation of Elliptic-Curve Point-Multiplication. They were able to show that power analysis attacks were indeed feasible on FPGAs.
Analyzing Biases in Human Perception of User Age and Gender from Text

User traits disclosed through written text, such as age and gender, can be used to per-sonalize applications such as recommender systems or conversational agents. However, human perception of these traits is not perfectly aligned with reality. In this paper, we conduct a large-scale crowdsourcing ex-periment on guessing age and gender from tweets. We systematically analyze the quality and possible biases of these predictions. We identify the textual cues which lead to miss-assessments of traits or make annotators more or less conﬁdent in their choice. Our study demonstrates that differences be-tween real and perceived traits are noteworthy and elucidates inaccurately used stereotypes in human perception.
Customizing Properties of β-Chitin in Squid Pen (Gladius) by Chemical Treatments

The squid pen (gladius) from the Loligo vulgaris was used for preparation of β-chitin materials characterized by different chemical, micro- and nano-structural properties that preserved, almost completely the macrostructural and the mechanical ones. The β-chitin materials obtained by alkaline treatment showed porosity, wettability and swelling that are a function of the duration of the treatment. Microscopic, spectroscopic and synchrotron X-ray diffraction techniques showed that the chemical environment of the N-acetyl groups of the β-chitin chains changes after the thermal alkaline treatment. As a consequence, the crystalline packing of the β-chitin is modified, due to the intercalation of water molecules between β-chitin sheets. Potential applications of these β-chitin materials range from the nanotechnology to the regenerative medicine. The use of gladii, which are waste products of the fishing industry, has also important environmental implications.
Chapter 14 ON APPLICATIONS OF DENSITY TRANSFORMS FOR UNCERTAIN DATA MINING Applications to Classification and Outlier Detection

In this chapter, we will examine a general density-based approach for handling uncertain data. The broad idea is that implicit information about the errors can be indirectly incorporated into the density estimate. We discuss methods for constructing error-adjusted densities of data sets, and using these densities as intermediate representations in order to perform more accurate mining. We discuss the mathematical foundations behind the method and establish ways of extending it to very large scale data mining problems. As concrete examples of our technique, we show how to apply the intermediate density representation in order to accurately solve the classification and outlier detection problems. This approach has the potential in constructing intermediate representations as a broad platform for data mining applications.
Using mutual information for selecting features in supervised neural net learning

This paper investigates the application of the mutual information criterion to evaluate a set of candidate features and to select an informative subset to be used as input data for a neural network classifier. Because the mutual information measures arbitrary dependencies between random variables, it is suitable for assessing the "information content" of features in complex classification tasks, where methods bases on linear relations (like the correlation) are prone to mistakes. The fact that the mutual information is independent of the coordinates chosen permits a robust estimation. Nonetheless, the use of the mutual information for tasks characterized by high input dimensionality requires suitable approximations because of the prohibitive demands on computation and samples. An algorithm is proposed that is based on a "greedy" selection of the features and that takes both the mutual information with respect to the output class and with respect to the already-selected features into account. Finally the results of a series of experiments are discussed.
Antiproliferative Activity of T. welwitschii Extract on Jurkat T Cells In Vitro

Triumfetta welwitschii is a plant used traditionally for the treatment of fever and diarrhoea. Previous work has shown that T. welwitschii has antibacterial activity. The purpose of this study was to investigate T. welwitschii extract for anticancer activity against Jurkat T cells. The Jurkat T cell line is used to study acute T cell leukaemia. An antiproliferation assay, determination of induction of apoptosis, the determination of the effect of the combination of the extract and GSH, and effects of the extract on DNA leakage were conducted. T. welwitschii was found to decrease cell viability in a dose- and time-dependent manner. T. welwitschii caused apoptosis in the Jurkat T cells as shown by DNA fragmentation. When T. welwitschii was combined with reduced GSH, it was found that the growth of the Jurkat T cells was significantly reduced compared to untreated cells after 72 h of treatment. This was unexpected, as cancer cells have elevated levels of GSH compared to normal cells. The results of this study show that T. welwitschii is a potential source of compounds that may serve as leads for anticancer compounds.
RETROSPECTIVE: Wattch: A Framework for Architectural-level Power Analysis and Optimizations

Circa mid-1990s there are signs of trouble brewing on the microprocessor roadmap horizon. Traditional Dennard scaling is running out of steam. CPU architects can no longer count on process technologists and circuit designers to give them power reduction for free. Terms like switched capacitance, sub-threshold leakage and decoupling capacitors were entering the lexicon of architects. But they have no easy way to relate these low-level micro phenomena to high-level macro architectural decisions. This was the environment at the time when Wattch appeared on the scene, introducing a much needed quantitative approach to power to the CPU architecture research community. Power considerations were already prominent for researchers in circuits and design automation topic areas since the early 1990’s. By the late 1990’s, they were beginning to also be on the minds of computer architects but mostly in the context of low power designs for battery driven mobile or embedded systems. This was not yet a problem that highperformance CPU architects felt they needed to tackle as a primary constraint since thermal dissipation and power delivery costs were still manageable. Process technology scaling had not yet hit the “leakage barrier” that was soon going to prevent both voltage and gate oxide thickness reductions. Cross-chip communication (the finite speed of light! ) and the limits of instruction-level parallelism were the hot topics in the architecture community. The special issue of IEEE Computer in September 1997 [1] that resulted as a followup to a vigorous debate at ISCA’96, was focused on options for Billion Transistor CPUs. Other than a brief mention of power in the introductory editorial, the rest of the articles did not explicitly address the impending reality that power was going to be the primary limiter for performance for general purpose CPUs. But this was changing [2] and the awareness of power issues among CPU architects was ramping up rapidly. In fact the first Workshop on Power-Driven Microarchitecture was held in conjunction with ISCA’98 in Barcelona (in a small room with a small but highly engaged audience). We were excited about the opportunities to demonstrate how architectural techniques could mitigate power dissipation challenges and optimize power-performance tradeoffs, but a key hurdle was how to offer quantitative results on the promise and potential of different ideas. Early work in power-aware architecture would use “proxy metrics” to quantify benefits. For example, an earlier paper from Brooks and Martonosi considered narrow-bitwidth operations and offered results on how frequently such optimizations could be applied [3]. What was missing, however, was a holistic architecture-level power model that could be used to run simulations just as instructionlevel simulators were commonly used for quantifying the performance benefits of architectural proposals.
On least-squares regression with censored data

The semiparametric accelerated failure time model relates the logarithm of the failure time linearly to the covariates while leaving the error distribution unspecified. The present paper describes simple and reliable inference procedures based on the least-squares principle for this model with right-censored data. The proposed estimator of the vector-valued regression parameter is an iterative solution to the Buckley--James estimating equation with a preliminary consistent estimator as the starting value. The estimator is shown to be consistent and asymptotically normal. A novel resampling procedure is developed for the estimation of the limiting covariance matrix. Extensions to marginal models for multivariate failure time data are considered. The performance of the new inference procedures is assessed through simulation studies. Illustrations with medical studies are provided. Copyright 2006, Oxford University Press.
Findings from a Major Methodological Study

Research upon the fear of crime has grown substantially in recent years. From its very inception, this field has relied almost exclusively upon quantitative surveys, which have suggested that the fear of crime is a prevalent social problem. However, doubts about the nature of the instruments used to investigate this phenomenon have cumulatively raised the possibility that the fear of crime has been significantly misrepresented. Dealing with the epistemologkal, conceptual, operational and technical critiques of quantitative surveys in general and of fear of crime surveys in particular, this article suggests that our understanding of the fear of crime is a product of the way it has been researched rather than the way it is. As the aim of the research project under which this data was collected was to develop and design new quantitative questions, the article ends with some possible solutions to the epistemological, conceptual, operational and technical problems discussed which may improve future quantitative research in this field.