Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytotoxicity of Atriplex confertifolia

The search for cancer treatment continues to be a global effort. As part of this global effort, many natural products have been tested against cancer cell lines, mostly from tropically located plants. This study reports that extracts of Atriplex confertifolia (Torr. and Frem.) S. Watson (Chenopodiaceae), a native North American plant (also known as shadscale or saltbush), has significant bioactivity against human breast cancer cell lines MCF-7, MDA-MB 435, MDA-MB 231, and HeLa cells (cervical cancer cells). The bioactivity of A. confertifolia extracts on these cells lines was compared to an FDA-approved cancer drug (Onxol®) and an industry-standard leukocyte control cell line. Active portions of the extracts were found primarily in the polar fractions of the plant. A dose-response curve of the extracts displayed significant cell death similar to Onxol®. The plant extracts did not significantly inhibit the viability of the leukocyte cell line. In a timed study, over 90% of cell lines MDA-MB 435 and HeLa died after 24 hours. Cell death appears to result from apoptosis.
Induction of Classifiers through Non-Parametric Methods for Approximate Classification and Retrieval with Ontologies

This work concerns non-parametric approaches for statistical learning applied to the standard knowledge representation languages adopted in the Semantic Web context. We present methods based on epistemic inference that are able to elicit and exploit the semantic similarity of individuals in OWL knowledge bases. Specifically, a totally semantic and language-independent semi-distance function is introduced, whence also an epistemic kernel function for Semantic Web representations is derived. Both the measure and the kernel function are embedded in non-parametric statistical learning algorithms customized for coping with Semantic Web representations. Particularly, the measure is embedded in a k-Nearest Neighbor algorithm and the kernel function is embedded in a Support Vector Machine. The implemented algorithms are used to perform inductive concept retrieval and query answering. An experimentation on real ontologies proves that the methods can be effectively employed for performing the target tasks, and moreover that it is possible to induce new assertions that are not logically derivable.
Diverse Radiofrequency Sensitivity and Radiofrequency Effects of Mobile or Cordless Phone near Fields Exposure in Drosophila melanogaster

Introduction The impact of electromagnetic fields on health is of increasing scientific interest. The aim of this study was to examine how the Drosophila melanogaster animal model is affected when exposed to portable or mobile phone fields. Methods/Results Two experiments have been designed and performed in the same laboratory conditions. Insect cultures were exposed to the near field of a 2G mobile phone (the GSM 2G networks support and complement in parallel the 3G wide band or in other words the transmission of information via voice signals is served by the 2G technology in both mobile phones generations) and a 1880 MHz cordless phone both digitally modulated by human voice. Comparison with advanced statistics of the egg laying of the second generation exposed and non-exposed cultures showed limited statistical significance for the cordless phone exposed culture and statistical significance for the 900 MHz exposed insects. We calculated by physics, simulated and illustrated in three dimensional figures the calculated near fields of radiation inside the experimenting vials and their difference. Comparison of the power of the two fields showed that the difference between them becomes null when the experimental cylinder radius and the height of the antenna increase. Conclusions/Significance Our results suggest a possible radiofrequency sensitivity difference in insects which may be due to the distance from the antenna or to unexplored intimate factors. Comparing the near fields of the two frequencies bands, we see similar not identical geometry in length and height from the antenna and that lower frequencies tend to drive to increased radiofrequency effects.
Functional Interactions between DrosophilabHLH/PAS, Sox, and POU Transcription Factors Regulate CNS Midline Expression of the slit Gene

During Drosophila embryogenesis the CNS midline cells have organizing activities that are required for proper elaboration of the axon scaffold and differentiation of neighboring neuroectodermal and mesodermal cells. CNS midline development is dependent on Single-minded (Sim), a basic-helix-loop-helix (bHLH)-PAS transcription factor. We show here that Fish-hook (Fish), a Sox HMG domain protein, and Drifter (Dfr), a POU domain protein, act in concert with Single-minded to control midline gene expression. single-minded,fish-hook, and drifter are all expressed in developing midline cells, and both loss- and gain-of-function assays revealed genetic interactions between these genes. The corresponding proteins bind to DNA sites present in a 1 kb midline enhancer from theslit gene and regulate the activity of this enhancer in cultured Drosophila Schneider line 2 cells. Fish-hook directly associates with the PAS domain of Single-minded and the POU domain of Drifter; the three proteins can together form a ternary complex in yeast. In addition, Fish can form homodimers and also associates with other bHLH-PAS and POU proteins. These results indicate that midline gene regulation involves the coordinate functions of three distinct types of transcription factors. Functional interactions between members of these protein families may be important for numerous developmental and physiological processes.
Study on Applications of Information Filtering/ Retrieval Algorithms in Social Network

Social Network [1] is defined as a network of interactions or relationships, where the nodes consist of actors and the edges consist of the relationships or interactions between these actors. Information retrieval is used to get the relevant information needed viewing and ignoring an irrelevant data. Information Filtering is a tool to help people to find the most valuable information. So that the limited time spent for reading/listening/viewing can be spent for the most interesting and valuable documents. This paper discusses some of the applications of Information Filtering/Retrieval Algorithms in the field of Social Network.
Tau Protein Mediates APP Intracellular Domain (AICD)-Induced Alzheimer’s-Like Pathological Features in Mice

Amyloid precursor protein (APP) is cleaved by gamma-secretase to simultaneously generate amyloid beta (Aβ) and APP Intracellular Domain (AICD) peptides. Aβ plays a pivotal role in Alzheimer’s disease (AD) pathogenesis but recent studies suggest that amyloid-independent mechanisms also contribute to the disease. We previously showed that AICD transgenic mice (AICD-Tg) exhibit AD-like features such as tau pathology, aberrant neuronal activity, memory deficits and neurodegeneration in an age-dependent manner. Since AD is a tauopathy and tau has been shown to mediate Aβ–induced toxicity, we examined the role of tau in AICD-induced pathological features. We report that ablating endogenous tau protects AICD-Tg mice from deficits in adult neurogenesis, seizure severity, short-term memory deficits and neurodegeneration. Deletion of tau restored abnormal phosphorylation of NMDA receptors, which is likely to underlie hyperexcitability and associated excitotoxicity in AICD-Tg mice. Conversely, overexpression of wild-type human tau aggravated receptor phosphorylation, impaired adult neurogenesis, memory deficits and neurodegeneration. Our findings show that tau is essential for mediating the deleterious effects of AICD. Since tau also mediates Aβ-induced toxic effects, our findings suggest that tau is a common downstream factor in both amyloid-dependent and–independent pathogenic mechanisms and therefore could be a more effective drug target for therapeutic intervention in AD.
Brownian dynamics simulations of reversible reactions in one dimension

A Brownian dynamics algorithm is developed for simulating many‐body effects in one dimensional competitive reversible binding of otherwise noninteracting particles. It allows time steps hundreds of times larger than in conventional lattice random walks and enables us to simulate systems which are sufficiently large to approach the thermodynamic limit. The asymptotic long‐time behavior is compared with mean‐field predictions.
Gaze-based interaction with public displays using off-the-shelf components

Eye gaze can be used to interact with high-density information presented on large displays. We have built a system employing off-the-shelf hardware components and open-source gaze tracking software that enables users to interact with an interface displayed on a 55" screen using their eye movements. The system works at a viewing distance of 1 to 1.5 meters and requires a 30 second calibration procedure for every user. We demonstrate how it can be used to navigate a digital bulletin board display with several notes on top of each other. There are some technical challenges detecting the eyes when people are wearing glasses and when external light sources are present.
Terminology Finite-state Preprocessing for Computational LFG

This paper presents a technique to deal with multiword nominal terminology in a computational Lexical Functional Grammar. This method treats multiword terms as single tokens by modifying the preprocessing stage of the grammar (tokenization and morphological analysis), which consists of a cascade of two-level finite-state automata (transducers). We present here how we build the transducers to take terminology into account. We tested the method by parsing a small corpus with the without this treatment of multiword terms. The number of parses and parsing time decrease without affecting the relevance of the results. Moreover, the method improves the perspicuity of the analyses.
Minimum energy path planning for ad hoc networks

We introduce the minimum energy path planning (MEPP) problem of finding a path for a mobile node traveling from a source to a destination while communicating with at least one node from a set of stationary nodes in such a way that minimizes the transmission energy used in communication. We characterize this problem and introduce the discretized graph algorithm that finds an approximate path by discretizing the problem space to form a graph and performing a shortest path search from source to destination. We find algorithm parameters that allow energy efficient paths to be found in suitable time. Finally, we discuss how this algorithm can be extended to facilitate other considerations in the problem
Modularization of Protein Interaction Networks by Incorporating Gene Ontology Annotations

Recent computational analyses of protein interaction networks have attempted to understand cellular organizations, processes and functions. However, they have encountered difficulties due to unreliable interaction data and the complexity of the networks. In this paper, we propose the integration of protein interaction networks with gene ontology annotations for assessing the reliability of current protein-protein interaction data. The interaction reliability can be used for building weighted protein interaction networks. We apply an information flow-based modularization algorithm to the weighted protein interaction networks. Our experimental results show that the interaction reliability between two proteins is positively correlated to the likelihood of functional and locational associations. We finally demonstrate that our approach identifies accurate modules in the protein interaction networks with high statistical confidence with respect to biological function and cellular localization. Moreover, this algorithm outperforms our previous method (Cho et al., 2006) integrating with genetic co-expressional profiles
Can we date an artist's work from catalogue photographs?

Computer vision has addressed many problems in art, but has not yet looked in detail at the way artistic style can develop and evolve over the course of an artist's career. In this paper we take a computational approach to modelling stylistic change in the body of work amassed by Sir John “Kyffin” Williams, a nationally renowned and prolific Welsh artist. Using images gathered from catalogues and online sources, we use a leave-one-out methodology to classify paintings by year; despite the variation in image source, size, and quality we are able to obtain significant correlations between predicted year and actual year, and we are able to guess the age of the painting within 15 years, for around 70% of our dataset. We also investigate the incorporation of expert knowledge within this framework by consdering a subset of paintings chosen as exemplars by a scholar familiar with Williams' work.
An identity-based personal location system with protected privacy in IOT

The internet of things (IOT) has the same security requirements as traditional network, but according to the characteristics of its own, the internet of things also has some specific security features. Among these features, the flexibility of the network requires nodes to apply corresponding measures when scene changes. For example, in emergency situations (e.g. an accident occurs, and a doctor is needed), the location of the user is available, while under normal circumstances, the user's location information is confidential. This paper is in the background of the above scene to present an identity based system for personal location in emergency situations. The proposed system consists of registration subsystem, user authentication subsystem, policy subsystem and client subsystem. The system confirms the identity of the user through the user authentication subsystem and gets the level of the emergency through the policy subsystem. Then it can make sure that user's location information can be accessed only by some authorized user, and only when necessary. The proposed system strengthens the protection of the user's privacy while providing the location of the user, and prevents the disclosure of the users' information.
Deening Knowledge Layers for Textual Case-based Reasoning

Textual CBR applications deal with problems that have traditionally been addressed by the Information Retrieval community, namely the handling of textual documents. Since CBR is an AI technique, the questions arise as to what kind of knowledge may enhance the system, where this knowledge comes from, and how it contributes to the performance of such a system. We will address these questions in this paper by showing how the various pieces of knowledge available in a speciic domain can be utilized.
Repeat After Me, My Name is Javier: Immigrants English Prociency Improvement Four Years After Arrival

Proficiency in the host-country language is one of the most important assimilation dimensions for immigrants. This paper analyzes changes in the English proficiency of recent immigrants to Canada using a panel data of four years. Probit and ordered probit estimations show how specific characteristics relate to language proficiency improvement or decline. I use speaking abilities as an overall indicator of language proficiency and separate the sample according to immigrants’ initial level: basic, intermediate or advanced. Overall, immigrants show relatively small improvements in language proficiency in the first four years. Still, those arriving under the family immigrant category with an intermediate or advanced level are less likely to improve and more likely to decrease their English proficiency. These results suggest that newcomers in this category experience a particularly different environment in the host country. The effect is not statistically robust for immigrants with a basic knowledge of English.
Learner Modeling to Predict Real-Time Affect in Serious Games

In recent decades research on human emotion has revealed that affect plays a central role in human cognition. Historically, emotion was viewed as separate from cognition, and only recently has there been consensus that affect is a central component of rational behavior and social interaction (Forgas, Wyland, & Lahan, 2006). These findings have motivated the goal of designing affect-sensitive computer systems capable of recognizing and responding to users’ emotional states. This has led to the development of affective systems with a wide variety of capabilities and purposes, such as therapeutic virtual agents, mood detection of large social network groups, and empathetic tutorial systems (Picard, 1997). Applications such as these require that three critical decisions must be made to inform how affect will be modeled and detected: 1) How will affect be represented? 2) What signals will be used for affect detection? 3) How will affect predictions be utilized?
Designing visual analytics systems for organizational environments

We present research focused on designing visual analytics (VA) systems for workers in organizational environments. We focus on business analysts and asset managers, who work collaboratively to analyze information and make decisions. Through extensive investigations in two organizational environments, we found that these users struggle with managing and analyzing information from multiple perspectives. Their current tools lack support for aggregating, organizing, and sharing such information. To address their needs, we characterized their analytic workflows, extracted specific key knowledge actions for each task commonly found in these workflows, and designed and evaluated two visual analytics systems that support and encapsulate these knowledge actions. We provide design guidelines that should be used when designing visual analytics systems, and illustrate their effectiveness with two systems built by following them.
EYEDIAP Database: Data Description and Gaze Tracking Evaluation Benchmarks

The lack of a common benchmark for the evaluation of the gaze estimation task from RGB and RGB-D data is a serious limitation for distinguishing the advantages and disadvantages of the many proposed algorithms found in the literature. The EYEDIAP database intends to overcome this limitation by providing a common framework for the training and evaluation of gaze estimation approaches. In particular, this database has been designed to enable the evaluation of the robustness of algorithms with respect to the main challenges associated to this task: i) Head pose variations; ii) Person variation; iii) Changes in ambient and sensing conditions and iv) Types of target: screen or 3D object. This technical report contains an extended description of the database, we include the processing methodology for the elements provided along with the raw data, the database organization and additional benchmarks we consider relevant to evaluate diverse properties of a given gaze estimator.
Telugu emotional story speech synthesis using SABLE markup language

In this paper, a framework for synthesizing Telugu emotional speech for story telling applications is presented. An XML based markup langauge, SABLE is used to synthesize the emotions from a given story text. SABLE markup defines a set of tags to improve the quality of the synthesized speech from the concatinative speech synthesizer. In this work, a subset of prosody tags are used to synthesize the emotional speech from a given story text. Modified Zero frequency filtered (ZFF) signal is used to derive the prosody correlates of pitch base, pitch range and intensity. The desired prosody modification factors for each emotion is derived at phrase level. The derived prosody modification parameters for each emotion are stored in the form of a template. During synthesis, hand annotated story text is replaced by prosody tags which are stored in templates. Prosody tagged story text at phrase level is automatically converted into SABLE markup format. The markup story text is used to synthesize emotional speech from the Telugu neutral Festival TTS system. The quality and naturalness of the synthesised emotional story speech is evaluated using subjective tests.
A Dynamic General Equilibrium Model of International Migration

The purpose of this paper is to introduce a dynamic version of the global trade and migration model (GMig2), which has been modified to include undocumented, unskilled workers in the United States. The development of a dynamic model is important because migration policy interacts with changes in population. The U.S. is consider in our model because a significant importer of migrant labor and in particular undocumented workers. We consider policies related to combinations of the following policy scenarios: increased border control, one-time legalization (Amnesty), and increasing the quota of undocumented workers.
Computational Efficient Scheme for Real Time Artifact-Free Image Up-Scaling

: Image upscaling, or single image super-resolution has recently become a hot topic in computer vision and computer graphics communities due to the increasing number of practical applications of the algorithms proposed. The problem of creating artifact-free upscaled images appearing natural and sharp to the human observer is probably more interesting and less trivial than it may appear. The solution to this problem, often referred to as “single image super-resolution”, is related both to the statistical relationship between high resolution and low resolution image sampling and to the human perception of image quality. In many practical applications, simple linear or cubic interpolation algorithms are applied for this task, but the results obtained are not really satisfactory, being affected by relevant artifacts like blurring. Several methods have been proposed to obtain better results, involving simple heuristics, edge modeling or statistical learning. The most powerful ones, however, present a high computational complexity and are not suitable for real time applications, while fast methods, even if edge-adaptive, are not able to provide artifacts-free images. Hear we describe adaptive and nonadaptive techniques such as NEDI and ICBI methods out of these the first one is well known interpolation method providing good results but computationally heavy (NEDI ). The high quality of the images enlarged with the new method is demonstrated with objective and subjective tests. The second method is a new up scaling method Iterative Curvature Based Interpolation (ICBI), based on a two step grid filling and an iterative correction of the interpolated pixels obtained by minimizing an objective function depending on the second order directional derivatives of the image intensity. We show that the constraints used to derive the function are related with those applied in another , while the computation time is reduced of 1-2 orders of magnitude with respect to NEDI, so that we were able, using a GPU implementation Using GUI (Graphical User Interface), to obtain real time performances.