Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Metabolomics to Understand the Aggressive Phenotype and Identify Novel Therapeutic Targets in Glioblastoma

Glioblastoma continues to be an invariably fatal malignancy. The established approach for understanding the biology of these aggressive tumors in an effort to identify novel molecular targets has largely been genotype-based. Unfortunately, clinical gains offered by this level of understanding have been limited, largely based on the complex nature of signaling networks associated with tumorigenesis and the inability to delineate the key “functional” signaling pathways actually driving growth in an individual tumor. Metabolomics is the global quantitative assessment of endogenous metabolites within a biological system, taking into account genetic regulation, altered kinetic activity of enzymes, and changes in metabolic reactions. Thus, compared to genomics and proteomics, metabolomics reflects changes in phenotype and therefore function. In this review, we highlight some of the key advancements that have been made in applying metabolomics to understand the aggressive phenotype of glioblastoma. Collectively, these studies have provided a previously unrecognized window into the underlying biology of these tumors. Current and future efforts are designed to determine how this technology may be applied to improve diagnosis and predict the aggressiveness of glioblastoma, and more importantly, identify novel, therapeutic strategies designed to improve clinical outcomes.
A Game Theoretic Approach toward Multi-Party Privacy-Preserving Distributed Data Mining

Analysis of privacy-sensitive data in a multi-party environment often assumes that the parties are well-behaved and they abide by the protocols. Parties compute whatever is needed, communicate correctly following the rules, and do not collude with other parties for exposing third party sensitive data. This paper argues that most of these assumptions fall apart in real-life applications of privacy-preserving distributed data mining (PPDM). The paper offers a more realistic formulation of the PPDM problem as a multi-party game where each party tries to maximize its own objectives. It offers a game-theoretic framework for developing and analyzing new robust PPDM algorithms. It also presents equilibrium-analysis of such PPDM-games and outlines a game-theoretic solution based on the concept of “cheap-talk” borrowed from the economics and the game theory literature.
A performance study of Fractional Frequency Reuse in OFDMA networks

Long Term Evolution (LTE) technology is considered as the most possible candidate for next generation mobile communications. LTE networks offer high capacity and are specified and designed to accommodate small, high performance, power-efficient end-user devices. One limiting factor that influences LTE performance is the interference from neighbor cells, the so called Inter-Cell Interference (ICI). Fractional Frequency Reuse (FFR) has been proposed as a technique to overcome this problem, since it can efficiently utilize the available frequency spectrum. This paper analyzes the FFR scheme and proposes a dynamic FFR mechanism that selects the optimal frequency allocation based on the cell total throughput and user satisfaction. In detail, the mechanism divides the cell into two regions (inner and outer) and selects the optimal size as well as the optimal frequency allocation between these regions with main target to maximize the overall throughput and user satisfaction. The mechanism is evaluated through several simulation scenarios that incorporate users' mobility.
Y2K: Myth or Reality?

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. We examine the valuation effects to Y2K-r elated announcements. We find that the announcement-day abnormal return is not significantly different from zero for the whole sample. Firms announcing the attainment of a Y2K-related contract , however, experience a statistically significant abnormal return of 0. 76 percent on the day of the announcement. In contrast, firms that announce that they are Y2K-ready experience a statistically significant negative abnormal return of-0.36 percent on the announcement day. For these companies, regression analysis reveals that abnormal returns are higher the more a firm spent on fixing or preventing Y2K-r elated problems. Furthermore, Y2K-ready stocks have outperformed industry peers following the year 2000 both in terms of operating and stock return performance. The evidence suggests that investors understood the severity of the problem and were able to distinguish between companies for which the issue was important and those for which it was not.
InterProScan: protein domains identifier

InterProScan [E. M. Zdobnov and R. Apweiler (2001) Bioinformatics, 17, 847–848] is a tool that combines different protein signature recognition methods from the InterPro [N. J. Mulder, R. Apweiler, T. K. Attwood, A. Bairoch, A. Bateman, D. Binns, P. Bradley, P. Bork, P. Bucher, L. Cerutti et al. (2005) Nucleic Acids Res., 33, D201–D205] consortium member databases into one resource. At the time of writing there are 10 distinct publicly available databases in the application. Protein as well as DNA sequences can be analysed. A web-based version is accessible for academic and commercial organizations from the EBI (). In addition, a standalone Perl version and a SOAP Web Service [J. Snell, D. Tidwell and P. Kulchenko (2001) Programming Web Services with SOAP, 1st edn. O'Reilly Publishers, Sebastopol, CA, ] are also available to the users. Various output formats are supported and include text tables, XML documents, as well as various graphs to help interpret the results.
The effect of haptic guidance on curve negotiation behavior of young, experienced drivers

Haptic feedback on the steering wheel is reported in literature as a promising way to support drivers during steering tasks. Haptic support allows drivers to remain in the direct manual control loop, avoiding known human factors issues with automation. This paper proposes haptic guidance based on the concept of shared control, where both the driver and the support system influence the steering wheel torque. The haptic guidance is developed to continuously generate relatively low forces on the steering wheel, requiring the driver's active steering input to safely negotiate curves. An experiment in a fixed-base driving simulator was conducted, in which 12 young, experienced drivers steered a vehicle - with and without haptic guidance - at a fixed speed along a road with varying curvature. The haptic guidance allowed drivers to slightly but significantly improve safety boundaries in their curve negotiation behavior. Their steering activity was reduced and smoother. The results indicated that continuous haptic guidance is a promising way to support drivers in actively producing (more) optimal steering actions during curve negotiation.
Non-Uniform Deblurring in HDR Image Reconstruction

Hand-held cameras inevitably result in blurred images caused by camera-shake, and even more so in high dynamic range imaging applications where multiple images are captured over a wide range of exposure settings. The degree of blurring depends on many factors such as exposure time, stability of the platform, and user experience. Camera shake involves not only translations but also rotations resulting in nonuniform blurring. In this paper, we develop a method that takes input non-uniformly blurred and differently exposed images to extract the deblurred, latent irradiance image. We use transformation spread function (TSF) to effectively model the blur caused by camera motion. We first estimate the TSFs of the blurred images from locally derived point spread functions by exploiting their linear relationship. The scene irradiance is then estimated by minimizing a suitably derived cost functional. Two important cases are investigated wherein 1) only the higher exposures are blurred and 2) all the captured frames are blurred.
Variational classification for visualization of 3D ultrasound data

We present a new technique for visualizing surfaces from 3D ultrasound data. 3D ultrasound datasets are typically fuzzy, contain a substantial amount of noise and speckle, and suffer from several other problems that make extraction of continuous and smooth surfaces extremely difficult. We propose a novel opacity classification algorithm for 3D ultrasound datasets, based on the variational principle. More specifically, we compute a volumetric opacity function that optimally satisfies a set of simultaneous requirements. One requirement makes the function attain nonzero values only in the vicinity of a user-specified value, resulting in soft shells of finite, approximately constant thickness around isosurfaces in the volume. Other requirements are designed to make the function smoother and less sensitive to noise and speckle. The computed opacity function lends itself well to explicit geometric surface extraction, as well as to direct volume rendering at interactive rates. We also describe a new splatting algorithm that is particularly well suited for displaying soft opacity shells. Several examples and comparisons are included to illustrate our approach and demonstrate its effectiveness on real 3D ultrasound datasets.
Quality and Reliability Engineering International Scalable Chi-square Distance versus Conventional Statistical Distance for Process Monitoring with Uncorrelated Data Variables

Multivariate statistical process control charts are often used for process monitoring to detect out-of-control anomalies. However, multivariate control charts based on conventional statistical distance measures, such as the one used in the Hotelling's T 2 control chart, cannot scale up to large amounts of complex process data, e.g. data with a large number of variables and a high rate of data sampling. In our previous work we developed a multivariate statistical process monitoring procedure based on a more scalable chi-square distance measure and tested this procedure for detecting out-of control anomalies—intrusions—in a computer process using computer audit data. The testing results demonstrated the comparable performance of the scalable chi-square procedure to that of Hotelling's T 2 control chart. To establish the chi-square procedure as a generic, viable multivariate statistical processing monitoring procedure, we conduct a series of further studies to understand the detection power and limitations of the chi-square procedure for processes with various kinds of data and various types of out-of-control anomalies in addition to the scalability and demonstrated performance of the chi-square procedure for computer intrusion detection. This paper reports on one of these studies that investigates the effectiveness of the scalable chi-square procedure in detecting out-of-control anomalies in processes with uncorrelated data variables, each of which has a normal probability distribution. The results of this study indicate that the chi-square procedure is at least as effective as Hotelling's T 2 control chart for monitoring processes with uncorrelated data variables.
Different patterns of human discrimination learning for two interaural cues to sound-source location

Two of the primary cues used to localize the sources of sounds are interaural level differences (ILDs) and interaural time differences (ITDs). We conducted two experiments to explore how practice affects the human discrimination of values of ILDs and ongoing ITDs presented over headphones. We measured discrimination thresholds of 13 to 32 naive listeners in a variety of conditions during a pretest and again, 2 weeks later, during a posttest. Between those two tests, we trained a subset of listeners 1 h per day for 9 days on a single ILD or ITD condition. Listeners improved on both ILD and ITD discrimination. Improvement was initially rapid for both cue types and appeared to generalize broadly across conditions, indicating conceptual or procedural learning. A subsequent slower-improvement stage, which occurred solely for the ILD cue, only affected conditions with the trained stimulus frequency, suggesting that stimulus processing had fundamentally changed. These different learning patterns indicate that practice affects the attention to, or low-level encoding of, ILDs and ITDs at sites at which the two cue types are processed separately. Thus, these data reveal differences in the effect of practice on ILD and ITD discrimination, and provide insight into the encoding of these two cues to sound-source location in humans.
How To Increase Public E-Services Usage In Governments - A Case Study Of The German Federal Employment Agency

E-services have been gaining increasing importance in the public sector over recent years. But even though e-services help governments in many ways – for example by increasing agency efficiency or enabling citizens to participate in democratic processes – citizen e-services usage rates still lag behind expectations in many countries to date. This article analyzes the reasons why citizens do not use e-government services more extensive and investigates how governments could increase usage. In a case study with the German Federal Employment Agency, we find that public institutions and their employees underestimate the willingness among citizens to use e-services, that citizens lack information about e-services, and that usability problems prevent citizens to use e-services more extensive. Furthermore, we evaluate three actions that have to be addressed to increase e-services usage among citizens.
Constructing a Collaborative Critique-Learning Environment for Exploring Science Through Improvisational Performance

This exploratory design experiment investigates Black male youth’s participation in a science-learning environment designed to conceptualize the practice of critique as improvisational performance. The research highlights the young men’s deployment of a linguistic practice, signifying, used to co-construct and enact the practice of collaborative critique. Implications include calling for the continued reimagining of teaching and learning science within urban contexts, including the need for educators to develop the required skills for recognizing and building upon students’ potential resources. The theoretical and pedagogical choices incorporated in this study contrasts often-utilized discourses of deficiency associated with science education in urban contexts.
Security and Privacy in Smart Grid Infrastructures

Adding digital intelligence and two-way functionalities to the power grid is one of the most flourishing topics in both academic and public institution communities. Efficiency, improved reliability and safety are the benefits promised by the new smart grid at the price of privacy and security challenges which are only in part similar to the security issues of IT networks. We survey the current grid architecture and the relation among the smart grid operators to analyze the security and privacy threats which needs to be addressed to secure the smart grid digital infrastructure.
Gene expression profiling by estimating parameters of gene regulatory network using meta-heuristics: A comparative study

Genes are present in the nucleus of every cell in an organism. Genes, metabolites, proteins and other by-products of cellular activity form a signaling pathway or network which is called a Gene Regulatory Network. Computational reconstruction of the network may uncover potential genetic causes of diseases and may aid drug detection. Advancements in biotechnology and image processing tools have made time series gene expression data available to researchers of computational biology. Reconstruction of Gene Regulatory Network has found a new direction with the availability of this data. After being processed by different statistical methods, the time series data may be considered as a matrix with each row representing a gene and each column representing a time point. The data suffers from an insufficiency of number of columns in relation to number of rows. This makes the reconstruction process more tedious. The problem is known as Curse of Dimensionality problem. The methods which are described here take processed microarray gene expression data as the input and produce the simulated gene expression time series with larger number of columns having regular small intervals. Gene Regulatory Network is reconstructed in the framework of Recurrent Neural Network. The parameters of the network are iteratively optimized using efficient local search optimization algorithms, namely two variants of Simulated Annealing and Tabu Search. The optimized parameters are used for the comparative study between the three methods in producing the time behavior or expression profiles of the genes. For almost all genes, the simulated profiles closely correspond to the original profiles.
What predicts the willingness of heterosexual persons to behave in a positive or negative manner towards homosexual persons

Unatoc mnogobrojnim spoznajama o odrednicama stavova i predrasuda prema gejevima i lezbijkama, manje istraživacke pažnje je posveceno odrednicama namjere ponasanja prema ovoj seksualnoj manjini. Cilj ovog istraživanja bio je po prvi puta na nasim prostorima sveobuhvatno ispitati cinitelje povezane s necijom sklonosti da diskriminira gejeve i lezbijke (negativno ponasanje) odnosno s necijom spremnosti da se ukljuci u aktivnosti usmjerene na poboljsanje drustvenog statusa homoseksualnih osoba (pozitivno ponasanje). Zanimalo nas je predviđaju li socio-demografske karakteristike koje su se pokazale važnim prediktorima stavova prema homoseksualnim osobama, poput roda, dobi, stupnja obrazovanja, religioznosti i politickog opredjeljenja, i namjeru pozitivnog i negativnog ponasanja prema njima. Dodatni cilj bio je ispitati ulogu i direktnog i indirektnog kontakta s gejevima i lezbijkama u predviđanju namjere ponasanja prema njima. Istraživanje je provedeno on-line, a u njemu je sudjelovalo 997 heteroseksualnih osoba. Skalama konstruiranima za potrebe ovog istraživanja ispitali smo sklonost diskriminaciji homoseksualnih osoba, spremnost na ukljucivanje u aktivnosti usmjerene na poboljsanje njihovog drustvenog statusa, direktni i indirektni kontakt s gejevima i lezbijkama, te socio-demografske karakteristike. Rezultati pokazuju kako su sudionici donekle skloni diskriminirati homoseksualne osobe u podrucju politike, radnog života i stanarskih prava, te kako nisu posebno spremni ukljuciti se u aktivnosti usmjerene na poboljsanje njihovog statusa, posebno kada se radi o aktivnostima u koje moraju uložiti vise truda i koje ukljucuju direktni kontakt s gejevima i lezbijkama. Vecu sklonost diskriminaciji pokazali su muskarci, starije osobe, religioznije osobe, osobe desnijeg politickog opredjeljenja i osobe s manje direktnog kontakta s gejevima i lezbijkama. Vecu spremnost na ukljucivanje u pozitivne aktivnosti pokazale su žene, manje religioznije osobe, oni lijevijeg politickog opredjeljenja te osobe s vise direktnog i indirektnog kontakta s gejevima i lezbijkama. Rezultati su dodatno raspravljeni u svjetlu njihovih prakticnih implikacija za edukativne i preventivne programe usmjerene na smanjivanje diskriminacije odnosno povecanje jednakosti homoseksualnih osoba u drustvu.
Estimating seed and pollen movement in a monoecious plant: a hierarchical Bayesian approach integrating genetic and ecological data

The scale of seed and pollen movement in plants has a critical influence on population dynamics and interspecific interactions, as well as on their capacity to respond to environmental change through migration or local adaptation. However, dispersal can be challenging to quantify. Here, we present a Bayesian model that integrates genetic and ecological data to simultaneously estimate effective seed and pollen dispersal parameters and the parentage of sampled seedlings. This model is the first developed for monoecious plants that accounts for genotyping error and treats dispersal from within and beyond a plot in a fully consistent manner. The flexible Bayesian framework allows the incorporation of a variety of ecological variables, including individual variation in seed production, as well as multiple sources of uncertainty. We illustrate the method using data from a mixed population of red oak (Quercus rubra, Q. velutina, Q. falcata) in the NC piedmont. For simulated test data sets, the model successfully recovered the simulated dispersal parameters and pedigrees. Pollen dispersal in the example population was extensive, with an average father–mother distance of 178 m. Estimated seed dispersal distances at the piedmont site were substantially longer than previous estimates based on seed‐trap data (average 128 m vs. 9.3 m), suggesting that, under some circumstances, oaks may be less dispersal‐limited than is commonly thought, with a greater potential for range shifts in response to climate change.
Maintaining quality of service for adaptive mobile map clients

In this paper we present the implementation of an adaptive mobile map client. We used a client-proxy-server model that enables the map client to activate and deactivate a set of filters managed by the proxy. We developed three map generalization filters each of which reduces the amount of data received by the map client using a different technique. A set of experiments and their results are discussed along with some heuristics that we believe could help optimize the use of the system.
Real-time tissue deformation and image rendering for computer simulation

Application of Virtual Reality (VR) has attracted many researchers in computer simulation fields. In this paper, an improved mass-spring model is proposed aiming at realistic simulation of tissue deformation. Firstly, virtual springs are proposed to represent the surface. Secondly, Verlet integration is applied to calculate the position of mass points during deformation without explicit computation of their velocities. Finally, a bilinear interpolation method is employed to generate a smooth mesh to render the deformed surface. The proposed method has been implemented using OpenGL which generates realistic deformation images in real-time.
ForAVis: explorative user forum analysis

User generated textual content on the internet has become increasingly valueable during the past few years. Forums, blogs, twitter and other social media websites are accessible for a huge amount of people all over the world. Hence, methods and tools are needed to handle this vast bulk of textual data. In this paper we present an explorative forum analysis system helping various stakeholders to cope with the task analyzing user generated content in online forums. The used mobile communication forums picture an example of user generated content in online discussion forums. Central to our system is a flexible visualization, which supports the analysis and exploration visually. Flexible means, that the ordering and the mapping of colors can be interactively changed by the analyst and the visualization is also capable to show the different structural levels of a user forum. The filter area offers beside well-known features many interesting features with respect to forum analysis, which we introduce in this paper. A detailed view of the particularly selected thread in the main visualization is presented in a third area. For a convenient manipulation and interaction we implemented intuitive mechanism. We describe the system and present various fictive user scenarios of different typical stakeholder tasks to illustrate the benefit of the system.