Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Bootstrapping Framework for Corpus Semantic Tagging

Availability of source information for semantic tagging (or disambignating) words in corpora is problematic. A framework to produce a semantically tagged corpus in a domain specific perspective using as source a general purpose taxonomy (i.e. WordNet) is here proposed. The tag set is derived from higher level Wordnet synsets. A methodology aiming to support semantic bootstrapping in a NLP application is defined. Results from large scale experiments are reported 1.
FuzzyProbSim: Fuzzy probability as similarity measure

This study investigates a unified robust measures of similarity applicable in many domains and across many dimensions of data. Given a distance or discrepancy measure on a domain, the similarity of two values in this domain is defined as the probability that any pair of values from that domain are more different (at a larger distance) than these two values are. Fuzzy sets are introduced to make this definition more sensitive to quantitative difference. Combination across domains is also discussed.
Information Technologies for Interoperability

Information systems largely involve networking these days. The development of complex business applications is now focused on an assembly of components available on a local area network or on the net. These components must be localized and identified in terms of available services and communication protocol before any request. This article presents the most common technologies that allow heterogeneous and distributed software systems to collaborate. The first part of the article introduces the base concepts of components and middleware while the following sections describe the different up-to-date models of communication and interaction and their use in industrial applications. To finish, the last section shows how different models can themselves communicate.
Cyclic strain induces dual-mode endothelial-mesenchymal transformation of the cardiac valve

Endothelial-mesenchymal transformation (EMT) is a critical event for the embryonic morphogenesis of cardiac valves. Inducers of EMT during valvulogenesis include VEGF, TGF-β1, and wnt/β-catenin (where wnt refers to the wingless-type mammary tumor virus integration site family of proteins), that are regulated in a spatiotemporal manner. EMT has also been observed in diseased, strain-overloaded valve leaflets, suggesting a regulatory role for mechanical strain. Although the preponderance of studies have focused on the role of soluble mitogens, we asked if the valve tissue microenvironment contributed to EMT. To recapitulate these microenvironments in a controlled, in vitro environment, we engineered 2D valve endothelium from sheep valve endothelial cells, using microcontact printing to mimic the regions of isotropy and anisotropy of the leaflet, and applied cyclic mechanical strain in an attempt to induce EMT. We measured EMT in response to both low (10%) and high strain (20%), where low-strain EMT occurred via increased TGF-β1 signaling and high strain via increased wnt/β-catenin signaling, suggesting dual strain-dependent routes to distinguish EMT in healthy versus diseased valve tissue. The effect was also directionally dependent, where cyclic strain applied orthogonal to axis of the engineered valve endothelium alignment resulted in severe disruption of cell microarchitecture and greater EMT. Once transformed, these tissues exhibited increased contractility in the presence of endothelin-1 and larger basal mechanical tone in a unique assay developed to measure the contractile tone of the engineered valve tissues. This finding is important, because it implies that the functional properties of the valve are sensitive to EMT. Our results suggest that cyclic mechanical strain regulates EMT in a strain magnitude and directionally dependent manner.
Performance analysis of a recursive fractional super-exponential algorithm

The super-exponential algorithm is a block-based technique for blind channel equalization and system identification. Due to its fast convergence rate, and no a priori parameterization other than the block length, it is a useful tool for linear equalization of moderately distortive channels. This paper presents a recursive implementation of the super-exponential algorithm for fractionally-sampled PAM signals. Although the resulting algorithm is still block-based, recursive propagation of several key variables allows the block length to be significantly reduced without compromising the algorithm's accuracy or speed, thereby enhancing its ability to track channel variations. The convergence rate is only mildly influenced by specific channel responses, and oversampling provides smaller output variance and almost perfect tolerance to sampling errors. Simulation results demonstrate the effectiveness of the proposed technique.
Applying the Wizard-of-Oz framework to cooperative service discovery and configuration

This work describes how the Wizard-of-Oz framework can be applied to a service robotics scenario. A scenario called the home tour scenario involving a collaborative service discovery and configuration multimodal dialogue for the robot is described. The role of the Wizard operators producing dialogue and robot movements as well as the specific simulation tools used: the dialogue production tool and the joystick navigation tool are discussed. Some attention is paid to the pilot studies performed as a preparation for the unified home tour scenario.
Generating Multi-Sentence Lingual Descriptions of Indoor Scenes

This paper proposes a novel framework for generating lingual descriptions of indoor scenes. Whereas substantial efforts have been made to tackle this problem, previous approaches focusing primarily on generating a single sentence for each image, which is not sufficient for describing complex scenes. We attempt to go beyond this, by generating coherent descriptions with multiple sentences. Our approach is distinguished from conventional ones in several aspects: (1) a 3D visual parsing system that jointly infers objects, attributes, and relations; (2) a generative grammar learned automatically from training text; and (3) a text generation algorithm that takes into account the coherence among sentences. Experiments on the augmented NYU-v2 dataset show that our framework can generate natural descriptions with substantially higher ROGUE scores compared to those produced by the baseline.
Aspirin dose for the prevention of cardiovascular disease: a systematic review.

CONTEXT More than 50 million US adults take aspirin regularly for long-term prevention of cardiovascular disease, typically either 81 mg/d or 325 mg/d. Controversy remains regarding the most appropriate long-term daily dose. OBJECTIVE To review the mechanism of action of aspirin and the clinical literature for relationships among aspirin dosage, efficacy, and safety. EVIDENCE ACQUISITION A systematic review of the English-language literature was undertaken using MEDLINE and EMBASE (searched through February 2007) and the search term aspirin or acetylsalicylic acid and dose. The search was limited to clinical trials and was extended by a review of bibliographies of pertinent reports of original data and review articles. Published prospective studies using different aspirin dosages in the setting of cardiovascular disease were included. EVIDENCE SYNTHESIS Although pharmacodynamic data demonstrate that long-term aspirin dosages as low as 30 mg/d are adequate to fully inhibit platelet thromboxane production, dosages as high as 1300 mg/d are approved for use. In the United States, 81 mg/d of aspirin is prescribed most commonly (60%), followed by 325 mg/d (35%). The available evidence, predominantly from secondary-prevention observational studies, supports that dosages greater than 75 to 81 mg/d do not enhance efficacy, whereas larger dosages are associated with an increased incidence of bleeding events, primarily related to gastrointestinal tract toxicity. CONCLUSIONS Currently available clinical data do not support the routine, long-term use of aspirin dosages greater than 75 to 81 mg/d in the setting of cardiovascular disease prevention. Higher dosages, which may be commonly prescribed, do not better prevent events but are associated with increased risks of gastrointestinal bleeding.
A Novel Lossy Image Compression Method

In this paper, we propose and implement a new lossy method to compress a digital image. We perform technique like quantization, smoothing before applying our novel, simple addition based technique to compress the image. The image is divided into set of 4 × 4 blocks. The results are good and comparable to JPEG compression algorithm, particularly when image quality is high. The compression ratio in the proposed method is high when adjacent pixel values in the image are close, which is usual in real images.
Bright OB stars in the Galaxy. III. Constraints on the radial stratification of the clumping factor

Context. Recent results strongly challenge the canonical picture of massive star winds: various evidence indicates that currently accepted mass-loss rates, u M, may need to be revised downwards, by factors extending to one magnitude or even more. This is because the most commonly used mass-loss diagnostics are affected by “clumping” (small-scale density inhomogeneities), influencing our interpretation of observed spectra and fluxes. Aims. Such downward revisions would have dramatic consequences for the evolution of, and feedback from, massive stars, and thus robust determinations of the clumping properties and mass-loss rates are urgently needed. We present a first attempt concerning this objective, by means of constraining the radial stratification of the so-called clumping factor. Methods. To this end, we have analyzed a sample of 19 Galactic O-type supergiants/giants, by combining our own and archival data for Hα, IR, mm and radio fluxes, and using approximate methods, calibrated to more sophisticated models. Clumping has been included into our analysis in the “conventional” way, by assuming the inter-clump matter to be void. Because (almost) all our diagnostics depends on the square of density, we cannot derive absolute clumping factors, but only factors normalized to a certain minimum. Results. This minimum was usually found to be located in the outermost, radio-emitting region, i.e., the radio mass-loss rates are the lowest ones, compared to u M derived from Hα and the IR. The radio rates agree well with those predicted by theory, but are only upper limits, due to unknown clumping in the outer wind. Hα turned out to be a useful tool to derive the clumping properties inside r < 3 . 5R� . Our most important result concerns a (physical) difference between denser and thinner winds: for denser winds, the innermost region is more strongly clumped than the outermost one (with a normalized clumping factor of 4.1 ± 1.4), whereas thinner winds have similar clumping properties in the inner and outer regions. Conclusions. Our findings are compared with theoretical predictions, and the implications are discussed in detail, by assuming different scenarios regarding the still unknown clumping properties of the outer wind.
Vertically Stratified Ash-Limb Beetle Fauna in Northern Ohio

To better understand the diversity and ecology of indigenous arthropods at risk from the invasive emerald ash borer (Agrilus planipennis Fairmaire) in North American forests, saproxylic beetles (Insecta: Coleoptera) were reared from ash (Fraxinus sp.) limbs suspended in the canopy, ~10–17 m above the ground, and from those placed on the ground in a mature mixed hardwood forest. In total, 209 specimens from 9 families and 18 species were collected from 30.0 m2 of limbs. The generalist cerambycid Neoclytus acuminatus (Fabricius) was the most commonly captured taxon, followed by an assemblage of four exotic ambrosia beetles dominated by Xylosandrus crassiusculus (Motschulsky). Two species largely or entirely restricted to ash, the buprestid Agrilus subcinctus Gory and the curculionid Hylesinus aculeatus (Say), were collected as well. Although there were no differences in beetle richness, abundance, or density between limb positions, community composition differed significantly. This can be largely attributed to phloem and wood-feeding species (i.e., Cerambycidae and Buprestidae) being more common in the suspended limbs and ambrosia beetles being more numerous on the forest floor. Possible explanations for these patterns are discussed.
Total 4EBP1 Is Elevated in Liver of Rats in Response to Low Sulfur Amino Acid Intake

Translation initiation is known to be regulated by the binding of eukaryotic initiation factor 4E (eIF4E) by binding proteins (4EBPs), and there is evidence that amino acid deprivation and other cellular stresses upregulate 4EBP1 expression. To pursue the question of whether diets limited in an essential amino acid lead to induction of 4EBP1 expression in vivo, diets that varied in methionine and cystine content were fed to rats for 7 days, and 4EBP1 mRNA and protein levels and 4EBP1 phosphorylation state were determined. Total 4EBP1 mRNA and protein abundance increased in liver of rats with severely deficient intakes of sulfur amino acids (0.23% or 0.11% methionine without cystine) but not in animals with a less restricted intake of sulfur amino acids (0.11% methionine plus 0.35% cystine) but a similarly restricted intake of total diet (53 to 62% of control). The amount of 4EBP1 binding activity (α + β forms) was elevated in liver of rats fed sulfur amino acid-deficient diets, whereas the hyperphosphorylation of 4EBP1 was not affected by dietary treatment. Results suggest that changes in total 4EBP1 expression should be considered when examining mechanisms that attenuate protein synthesis during amino acid deficiency states.
Oligocene Termite Nests with In Situ Fungus Gardens from the Rukwa Rift Basin, Tanzania, Support a Paleogene African Origin for Insect Agriculture

Based on molecular dating, the origin of insect agriculture is hypothesized to have taken place independently in three clades of fungus-farming insects: the termites, ants or ambrosia beetles during the Paleogene (66–24 Ma). Yet, definitive fossil evidence of fungus-growing behavior has been elusive, with no unequivocal records prior to the late Miocene (7–10 Ma). Here we report fossil evidence of insect agriculture in the form of fossil fungus gardens, preserved within 25 Ma termite nests from southwestern Tanzania. Using these well-dated fossil fungus gardens, we have recalibrated molecular divergence estimates for the origins of termite agriculture to around 31 Ma, lending support to hypotheses suggesting an African Paleogene origin for termite-fungus symbiosis; perhaps coinciding with rift initiation and changes in the African landscape.
Beyond the Construction of Optimal switching surfaces for Autonomous Hybrid Systems

Abstract In this paper we report of a technique to design optimal feedback control laws for hybrid systems with autonomous (continuous) modes. Existing techniques design the optimal switching surfaces based on a singular sample evolution of the system; hence providing a solution dependent on the initial conditions. On the other hand, the optimal switching times can be found, providing an an open loop control to the system, but those also are dependent on the initial conditions. The technique presented relies on a variational approach, giving the derivative of the switching times with respect to the initial conditions, thus providing a tool to design programs/algorithms generating switching surfaces which are optimal for any possible execution of the system.
Stabilization of sliding mode controller for uncertain discrete-time-delayed nonlinear systems using descriptor approach

Control of nonlinear systems is vital due to wide range of their application. As it is obvious that the minimum requirement in any control system is the stability, however the proof of stability is not trivial in case of the nonlinear control systems. One of the best nonlinear control techniques is sliding mode control by applying a descriptor model transformation for bounding cross terms. Descriptor approach in sliding mode controller design for uncertain discrete time delayed nonlinear system is investigated in this paper.
Efficient Energy Management Using Adaptive Reinforcement Learning-Based Scheduling in Large-Scale Distributed Systems

Energy consumption in large-scale distributed systems, such as computational grids and clouds gains a lot of attention recently due to its significant performance, environmental and economic implications. These systems consume a massive amount of energy not only for powering them, but also cooling them. More importantly, the explosive increase in energy consumption is not linear to resource utilization as only a marginal percentage of energy is consumed for actual computational works. This energy problem becomes more challenging with uncertainty and variability of workloads and heterogeneous resources in those systems. This paper presents a dynamic scheduling algorithm incorporating reinforcement learning for good performance and energy efficiency. This incorporation helps the scheduler observe and adapt to various processing requirements (tasks) and different processing capacities (resources). The learning process of our scheduling algorithm develops an association between the best action (schedule) and the current state of the environment (parallel system). We have also devised a task-grouping technique to help the decision-making process of our algorithm. The grouping technique is adaptive in nature since it incorporates current workload and energy consumption for the best action. Results from our extensive simulations with varying processing capacities and a diverse set of tasks demonstrate the effectiveness of this learning approach.
On the prevention of collusion attack in OLSR-based Mobile Ad hoc Networks

A particularly severe attack on routing protocols in mobile ad hoc networks (MANETs) is the collusion attack, in which a pair of colluding attackers prevent routes to a specific node (targeted node) from being established. This attack has devastating impact on Optimized Link State Routing (OLSR) protocol which is one of the standard routing protocols for MANETs. When there is a collusion attack in the network, the simulation results show that the Packet Delivery Ratio (PDR) drops to 0% for the targeted node. In this paper, we present an efficient protocol to prevent the collusion attack, by incorporating an information theoretic trust framework in OLSR. This protocol tries to ascertain the presence of the colluding attackers by evaluating and quantifying their trust values based on their uncertainty measures. Entropy functions have been used to represent the uncertainty involved in a node¿s behavior. We call the proposed protocol as Collusion Attack Prevention-OLSR (CAP-OLSR). In CAP-OLSR, the targeted node requests neighbor nodes to make recommendations on doubtful attackers based on the nature of the attack. For this purpose two new messages called Trust Request (TREQ) and Trust Reply (TREP) have been added to the OLSR protocol. Simulation results show that CAP-OLSR can efficiently detect the colluding attackers and significantly improve the PDR of the nodes in the network. Our protocol has several advantages since it does not require any time synchronization or location information and shows significant improvement in PDR under various scenarios.
Human fibroblasts display a differential focal adhesion phenotype relative to chimpanzee

It has been documented that there are differences in disease susceptibilities between humans and non-human primates. We investigate one of these differences in fibroblasts to examine differences in cellular adhesion between humans and chimpanzees using microscopy and gene expression and have found significant differences in both datasets. These results suggest that human and chimpanzee fibroblasts may have somewhat different adhesive properties, which could play a role in differential disease phenotypes and responses to external factors.
Exact state and covariance sub-matrix recovery for submap based sparse EIF SLAM algorithm

This paper provides a novel state vector and covariance sub-matrix recovery algorithm for a recently developed submap based exactly sparse extended information filter (EIF) SLAM algorithm - sparse local submap joining filter (SLSJF). The algorithm achieves exact recovery instead of approximate recovery. The recovery algorithm is very efficient because of an incremental Cholesky factorization approach and a natural reordering of the global state vector. Simulation results show that the computation cost of the SLSJF is much lower as compared with the sequential map joining algorithm using extended Kalman filter (EKF). The SLSJF with the proposed recovery algorithm is also successfully applied to the Victoria Park data set.
Ontology model for complementary breastfeeding recipes

Complementary breastfeeding is food or a drink which contains nutrients given to children aged 6–24 month. A lot of information of complementary breastfeeding recipes cause confusion in creating a complementary breastfeeding menu. Hence ontology is considered as an appropriate approach in this case. The arranged ontology is able to describe information more systematically. It makes search and knowledge sharing easier and able to enrich the implementation of semantics technology. This research is focused on how to build an ontology model for complementary breastfeeding recipes. The result of this research is an ontology model for complementary breastfeeding recipes in OWL format. This ontology model of complementary breastfeeding recipes has nine major classes namely Bahan_Makanan, Bumbu, Cara_Olah, Jenis_Makanan, Kandungan_Gizi, Nama_Resep, Rasa_Makanan, Tekstur_Makanan and Usia_Bayi. The ontology model which has been created can answer the questions about complementary breastfeeding recipes correctly. The questions are tested through Quick Search and SPARQL testing and validated by experts nutritionists. This makes the ontology model for complementary breastfeeding recipes can be developed into wider ontology model.
A Low-Cost Mobile Urban Environmental Monitoring System

The increasing pace of economic development and urbanization around the world has led to serious problems of environmental pollution, particularly from automobile emissions which contributes to Global Warming. In this paper, a low-cost mobile urban environmental monitoring system is proposed using off-the-shelf open source hardware and software. The system can be installed or used in public transport vehicles, particularly in school and college buses in countries like India. A pollution map of local and regional environments can be built from the data acquired, and displayed online leading to increased awareness of urban pollution problems. The system can also be used in situ in school and college buses to educate children and youth on emerging technologies like computer hardware, software, and web technologies. Results of prototype implementation are presented to illustrate the effectiveness of the approach.
Investigation of control scheme based on stationary reference frame using three level space vector modulated grid connected inverter with NP balancing algorithm

In this paper a control scheme based on instantaneous reactive power theory for three phase three level grid connected inverter is presented. A fuzzy logic controller and a PR controller for the DC bus voltage and the current control are applied respectively. Space vector modulation for the switching pattern generation is used. The Space Vector modulation algorithm is improved via the utilization of a Neutral Point balancing technique, which results the performance enhancement of the inverter. Furthermore, the ability of the control system for uninterrupted compensation of the reactive power is investigated. The performance of the proposed electric power system is established using Matlab/Simulink.