Miracle-dz/UniFAR-FTUs huggingface dataset:
A game theoretical approach for cooperative green mobile operators under roaming price consideration

In this paper, we investigate the performance of a green mobile operator collaborating with other traditional mobile operators. Its goal is to minimize its CO2 emissions, maximize its profit or achieve or tradeoff between both objectives by offloading its users to neighbor networks and exploiting renewable energies. On the other hand, traditional mobile operators aim to maximize their profits by attracting the maximum number of roamed users. The problem is modeled as a two-level Stackelberg game and its equilibrium is derived. A green mobile operator level that determines how many users per each base station to offload to each neighbor network, and a non-green mobile operator level where operators focus on finding the optimal roaming price. Our simulation results show a significant saving in terms of CO2 emissions compared to the non-cooperation case and that roaming decision depends essentially on the availability of renewable energy in base station sites.
A methodology and tool for automated transformational high-level design space exploration

Objective of the methodology presented in this paper is to perform design space exploration on a high level of abstraction by applying high-level transformations. The paper concentrates on algorithmic approaches on controlling the iterative process of transformation selection. A novel modular algorithm for transformation control is presented and its effectiveness is experimentally validated. In combination with a large set of transformation algorithms and mechanisms for high-level estimation of transformation quality, there results a methodology for automated high-level design space exploration. All the concepts are summarized in a software tool called ExTra (Design Space Exploration Using Transformations). Finally, the results of the application of ExTra to the JPEG encoding algorithm are presented.
Modelling of air-mist spray cooling heat transfer for continuous slab casting

Abstract The spray cooling technology is a key technology in the continuous casting process, which has a significant influence on the surface quality. In order to ensure high quality standards at different operating conditions, modern continuous casting machines provide the possibility to vary the cooling with respect to intensity, width, stand off distances, etc. For calculating the cooling intensity in the engineering process and during caster operation, precise information about the cooling characteristics of spray nozzles is needed. The subject of the present work is the modelling of the spray cooling heat transfer using flat spray air mist nozzles. Measurements of the spray pattern and air/water flows were carried out on a spray test stand in order to investigate the profiles of the water flux density at different air / water pressures and different distances from the nozzle tip to the surface. The heat transfer coefficients due to spray cooling were measured using an experimental stand which allows experiments up to a surface temperature of 1250°C. Based on the obtained experimental data a heat transfer model for air mist sprays is developed to describe the effect of the different operating conditions on the spray cooling heat transfer coefficient.
Acute tolerance to narcotic analgesic drugs in rats.

It has been reported that treatment of rats and mice with actinomycin D, an antibiotic inhibitor of protein synthesis, diminishes the impairment of the analgesic effect of morphine normally observed during chronic treatment with the analgesic (Cohen, Keats, Krivoy & Ungar, 1965). The widespread metabolic disturbances that arise during prolonged treatment with inhibitors of protein synthesis (Young, Robinson & Sacktor, 1963) make it difficult to interpret this result, and in fact, some of the animals receiving higher doses of actinomycin died. In the experiments reported in the present paper it is shown that in rats, tolerance to morphine and other analgesics given by continuous intravenous infusion develops within 4 hr and this makes it possible to study the effects of actinomycin D on tolerance while overall metabolism is apparently unimpaired.
Bioie: Retargetable Information Extraction and Ontological Annotation of Biological Interactions from the Literature

The need for extracting general biological interactions of arbitrary types from the rapidly growing volume of the biomedical literature is drawing increased attention, while the need for this much diversity also requires both a robust treatment of complex linguistic phenomena and a method to consistently characterize the results. We present a biomedical information extraction system, BioIE, to address both of these needs by utilizing a full-fledged English grammar formalism, or a combinatory categorial grammar, and by annotating the results with the terms of Gene Ontology, which provides a common and controlled vocabulary. BioIE deals with complex linguistic phenomena such as coordination, relative structures, acronyms, appositive structures, and anaphoric expressions. In order to deal with real-world syntactic variations of ontological terms, BioIE utilizes the syntactic dependencies between words in sentences as well, based on the observation that the component words in an ontological term usually appear in a sentence with known patterns of syntactic dependencies.
Uncovering User Interaction Dynamics in Online Social Networks

Measurement studies of online social networks (OSNs)show that all social links are not equal, and the strength of each link is best characterized by the frequency of interactions between the linked users. To date, few studieshave been able to examine detailed interactiondata over time. In this paper, we first analyze the interaction dynamics in a large online social network. We find that users invite new friends to interact at a nearly constant rate, prefer to continue interacting with friends with whom they have a larger number of historical interactions,and most social links drop in interaction frequency over time. Then, we use our insights from the analysis to derive a generative model of social interactionsthat can capture fundamental processes underlinguser interactions.
Salient regions detection for indoor robots using RGB-D data

The goal of saliency detection is to highlight objects in image data that stand out relative to their surrounding. Therefore, saliency detection aims to capture regions that are perceived as important. The most recent bottom-up approaches for saliency detection measure contrast based on visual features in 2D scenes, ignoring depth value. This work presents an effective method to measure saliency by mapping pixels into foreground and background regions in RGB-D images. Namely, we first segment an image into regions to evaluate the object uniqueness and consistency using graph-based segmentation. Then, we utilize the region color, depth, layout and boundary information to produce robust foreground and background saliency measures. Finally, we combine the two saliency maps based on Gaussian weights. As a result, our approach produces high-quality saliency maps, which may be used for further processing like object detection or recognition. Experimental results on two datasets compare our method with the state of the art and highlight its effectiveness.
Predicting packet-loss visibility using scene characteristics

We examine the influence of scene-level content on the visibility of packet loss impairments in MPEG-2 and H.264 compressed video. We consider both global camera motion and proximity to a scene cut. We use Patient Rule Induction Method (PRIM) to pick out both highly visible and very invisible packet losses. We show that global camera motion significantly increases visibility relative to a still camera. Further, while packet losses that are concealed using a prior scene’s image are strongly visible, all other packet losses near a scene change are much less likely to be visible, all other factors being equal.
Evaluation of Texture Features for Offline Arabic Writer Identification

Biometric identification of persons has mainly been based on fingerprints, face, iris and other similar attributes. We propose a handwriting-based biometric identification system using a large database of Arabic handwritten documents. The system first extracts, from each handwritten sample, a set of features including run lengths, edge-hinge and edge-direction features. These features are used by a Multiclass SVM (Support Vector Machine) classifier. Experiments are conducted on a new large database of Arabic handwritings contributed by 1000 writers. The highest identification rate achieved by the combination of run-length and edge-hinge features stands at 84.10%.
Conditions under which Arousal Does and Does Not Elevate Height Estimates

We present a series of experiments that explore the boundary conditions for how emotional arousal influences height estimates. Four experiments are presented, which investigated the influence of context, situation-relevance, intensity, and attribution of arousal on height estimates. In Experiment 1, we manipulated the environmental context to signal either danger (viewing a height from above) or safety (viewing a height from below). High arousal only increased height estimates made from above. In Experiment 2, two arousal inductions were used that contained either 1) height-relevant arousing images or 2) height-irrelevant arousing images. Regardless of theme, arousal increased height estimates compared to a neutral group. In Experiment 3, arousal intensity was manipulated by inserting an intermediate or long delay between the induction and height estimates. A brief, but not a long, delay from the arousal induction served to increase height estimates. In Experiment 4, an attribution manipulation was included, and those participants who were made aware of the source of their arousal reduced their height estimates compared to participants who received no attribution instructions. Thus, arousal that is attributed to its true source is discounted from feelings elicited by the height, thereby reducing height estimates. Overall, we suggest that misattributed, embodied arousal is used as a cue when estimating heights from above that can lead to overestimation.
Stratos: Virtual Middleboxes as First-Class Entities

Enhancing application deployments in today’s clouds using virtual middleboxes is challenging due to the lack of network control and the inherent difficult in intelligently scaling middleboxes to cope with application demands. Our position is that application and middlebox composition and scaling must occur in concert, and addressing the challenges that arise requires a framework that recognizes middleboxes as first-class entities. In this paper, we present the design, implementation, and evaluation of such a framework, called Stratos, that is targeted for immediate deployment overor under-the-cloud today. In Stratos, tenants specify rich middlebox and application topologies using high-level abstractions, and desired middlebox traversals are realized using a novel distributed programmable data plane design. To avoid degradation in middlebox performance, middleboxes are automatically scaled using a greedy heuristic to meet application demands. Under-the-cloud deployments using networkaware flow distribution and placement provide further performance and scaling benefits. Our evaluation of an overthe-cloud deployment atop EC2 and simulation of an underthe-cloud deployment shows Stratos provides significant benefits to both tenants and providers.
Patent Ductus Venosus and Dioxin Resistance in Mice Harboring a Hypomorphic Arnt Allele*

The Ah receptor nuclear translocator (ARNT) is the dimeric partner of hypoxia-inducible factors and thus plays a pivotal role in cellular adaptation to low oxygen environments. ARNT is also a dimeric partner for the Ah receptor (AHR), and this complex is essential in regulating the adaptive metabolic response to polycyclic aromatic hydrocarbons. Because of the essential role of ARNT in hypoxia-driven developmental events, it has been difficult to study the physiological significance of AHR·ARNT heterodimers in vivo. To address this issue, we developed a hypomorphic Arnt allele that displayed normal development and allowed the examination of the role of ARNT in AHR biology. In this regard, the AHR is also known to mediate two additional biological processes: the toxicological response to compounds such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) and the developmental closure of a fetal vascular structure known as the ductus venosus. Although the mechanism of the adaptive pathway has been well described, the mechanism of AHR-mediated signal transduction in the toxic and developmental pathways is not well understood. Liver perfusion studies demonstrated that ARNT hypomorphs have a patent ductus venosus, identical to that observed in the Ahr null mice. Parallel dioxin toxicity studies demonstrated that the ARNT hypomorphs exhibited resistance to the end points of dioxin exposure. Moreover, we observed that toxicity could be segregated from the classical adaptive responses such as P4501A induction. Taken in sum, these experiments demonstrate that ARNT is an essential component of AHR developmental signaling and shed light on the mechanism of dioxin toxicity.
Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems

Aptamers, which can be screened via systematic evolution of ligands by exponential enrichment (SELEX), are superior ligands for molecular recognition due to their high selectivity and affinity. The interest in the use of aptamers as ligands for targeted drug delivery has been increasing due to their unique advantages. Based on their different compositions and preparation methods, aptamer-functionalized targeted drug delivery systems can be divided into two main categories: aptamer-small molecule conjugated systems and aptamer-nanomaterial conjugated systems. In this review, we not only summarize recent progress in aptamer selection and the application of aptamers in these targeted drug delivery systems but also discuss the advantages, challenges and new perspectives associated with these delivery systems.
The Marine Side of a Terrestrial Carnivore: Intra-Population Variation in Use of Allochthonous Resources by Arctic Foxes

Inter-individual variation in diet within generalist animal populations is thought to be a widespread phenomenon but its potential causes are poorly known. Inter-individual variation can be amplified by the availability and use of allochthonous resources, i.e., resources coming from spatially distinct ecosystems. Using a wild population of arctic fox as a study model, we tested hypotheses that could explain variation in both population and individual isotopic niches, used here as proxy for the trophic niche. The arctic fox is an opportunistic forager, dwelling in terrestrial and marine environments characterized by strong spatial (arctic-nesting birds) and temporal (cyclic lemmings) fluctuations in resource abundance. First, we tested the hypothesis that generalist foraging habits, in association with temporal variation in prey accessibility, should induce temporal changes in isotopic niche width and diet. Second, we investigated whether within-population variation in the isotopic niche could be explained by individual characteristics (sex and breeding status) and environmental factors (spatiotemporal variation in prey availability). We addressed these questions using isotopic analysis and Bayesian mixing models in conjunction with linear mixed-effects models. We found that: i) arctic fox populations can simultaneously undergo short-term (i.e., within a few months) reduction in both isotopic niche width and inter-individual variability in isotopic ratios, ii) individual isotopic ratios were higher and more representative of a marine-based diet for non-breeding than breeding foxes early in spring, and iii) lemming population cycles did not appear to directly influence the diet of individual foxes after taking their breeding status into account. However, lemming abundance was correlated to proportion of breeding foxes, and could thus indirectly affect the diet at the population scale.
Layered label propagation: a multiresolution coordinate-free ordering for compressing social networks

We continue the line of research on graph compression started with WebGraph, but we move our focus to the compression of social networks in a proper sense (e.g., LiveJournal): the approaches that have been used for a long time to compress web graphs rely on a specific ordering of the nodes (lexicographical URL ordering) whose extension to general social networks is not trivial. In this paper, we propose a solution that mixes clusterings and orders, and devise a new algorithm, called Layered Label Propagation, that builds on previous work on scalable clustering and can be used to reorder very large graphs (billions of nodes). Our implementation uses task decomposition to perform aggressively on multi-core architecture, making it possible to reorder graphs of more than 600 millions nodes in a few hours. Experiments performed on a wide array of web graphs and social networks show that combining the order produced by the proposed algorithm with the WebGraph compression framework provides a major increase in compression with respect to all currently known techniques, both on web graphs and on social networks. These improvements make it possible to analyse in main memory significantly larger graphs.
Virtual input devices for 3D systems

The device unified interface is a generalized and easily expandable protocol for the communication between applications and input devices. The key idea is to unify various device data into the parameters of a so-called "virtual input device. " The device information-base, which includes device dependent information, is also incorporated into the virtual input device. Using the device unified interface, system builders are able to design their applications independent of the input devices as well as utilize the capabilities of several devices in the same application. <<ETX>>
Sliding-Mode Control for Piezoelectric Actuators Based on Hysteresis Observer

A sliding-mode control (SMC) scheme based on hysteresis observer is designed in this paper for precision trajectory tracking of piezoelectric actuators. A mathematical model considering the dynamics of a mass-spring-damper trio and the hysteresis friction force describing the parameters of bristle stiffness, damping and viscous is proposed. A lumped uncertain function composed of the mechanical parameters, displacement and its deriviation, hysteresis friction force and external load force is estimated by a hysteresis observer. An asymptotically stable sliding surface is defined. Lyapunov stability theory is applied to guarantee the asymptotical stability for the trajectory tracking error. Experiments are conducted to validate the effectiveness of the proposed method. Results show that a satisfied tracking response to a sinusoidal trajectory is achieved, and the positioning errors under a triangle scanning contour are dramatically reduced compared with the traditional SMC.
Effect of Coupling Agent on the Properties of Polymer/Date Pits Composites

The morphology of the fracture surfaces of polymer/date pits composites was investigated. Polymers used in this study were high density polyethylene (HDPE) and polystyrene (PS). Date pits in the form of granules were two types of date pits: khlaas (K) and sekari (S). Two coupling agents, diphenylmethane-4 4′-diisocyanate (DPMI) and ethylene propylene grafted with malice anhydride (EP-g-MA), were used to ease the incorporation of date pit particles into polymer matrix. The SEM micrographs of the neat composites, that is, with no coupling agents, showed coarse morphology with bad dispersion, adhesion, and distribution of date pit particles within the polymer matrix. On the other hand, PS100/K composites coupled with DPMI and EP-g-MA had reasonable dispersed phase size with good distribution and adhesion to the composite matrix which in turn improve the mechanical properties of the resulted polymer/date pits composites.
Video search in concept subspace: a text-like paradigm

Though both quantity and quality of semantic concept detection in video are continuously improving, it still remains unclear how to exploit these detected concepts as semantic indices in video search, given a specific query. In this paper, we tackle this problem and propose a video search framework which operates like searching text documents. Noteworthy for its adoption of the well-founded text search principles, this framework first selects a few related concepts for a given query, by employing a tf-idf like scheme, called c-tf-idf, to measure the informativeness of the concepts to this query. These selected concepts form a concept subspace. Then search can be conducted in this concept subspace, either by a Vector Model or a Language Model. Further, two algorithms, i.e., Linear Summation and Random Walk through Concept-Link, are explored to combine the concept search results and other baseline search results in a reranking scheme. This framework is both effective and efficient. Using a lexicon of 311 concepts from the LSCOM concept ontology, experiments conducted on the TRECVID 2006 search data set show that: when used solely, search within the concept subspace achieves the state-of-the-art concept search result; when used to rerank the baseline results, it can improve over the top 20 automatic search runs in TRECVID 2006 on average by approx. 20%, on the most significant one by approx. 50%, all within 180 milliseconds on a normal PC.
Change in prevalence of chronic kidney disease in England over time: comparison of nationally representative cross-sectional surveys from 2003 to 2010

Objectives To determine whether the prevalence of chronic kidney disease (CKD) in England has changed over time. Design Cross-sectional analysis of nationally representative Health Survey for England (HSE) random samples. Setting England 2003 and 2009/2010. Survey participants 13 896 adults aged 16+ participating in HSE, adjusted for sampling and non-response, 2009/2010 surveys combined. Main outcome measure Change in prevalence of estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 (as proxy for stage 3–5 CKD), from 2003 to 2009/2010 based on a single serum creatinine measure using an isotope dilution mass spectrometry traceable enzymatic assay in a single laboratory; eGFR derived using Modified Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKDEPI) eGFR formulae. Analysis Multivariate logistic regression modelling to adjust time changes for sociodemographic and clinical factors (body mass index, hypertension, diabetes, lipids). A correction factor was applied to the 2003 HSE serum creatinine to account for a storage effect. Results National prevalence of low eGFR (<60) decreased within each age and gender group for both formulae except in men aged 65–74. Prevalence of obesity and diabetes increased in this period, while there was a decrease in hypertension. Adjustment for demographic and clinical factors led to a significant decrease in CKD between the surveyed periods. The fully adjusted OR for eGFR <60 mL/min/1.73 m2 was 0.75 (0.61 to 0.92) comparing 2009/2010 with 2003 using the MDRD equation, and was similar using the CKDEPI equation 0.73 (0.57 to 0.93). Conclusions The prevalence of a low eGFR indicative of CKD in England appeared to decrease over this 7-year period, despite the rising prevalence of obesity and diabetes, two key causes of CKD. Hypertension prevalence declined and blood pressure control improved but this did not appear to explain the fall. Periodic assessment of eGFR and albuminuria in future HSEs is needed to evaluate trends in CKD.