Miracle-dz/UniFAR-FTUs huggingface dataset:
Burn injury differentially alters whole-blood and organ glutathione synthesis rates: An experimental model

Previous studies from our laboratories revealed a reduced rate of whole-blood (WB) glutathione (GSH) synthesis in severely burned patients. To determine whether WB GSH metabolism is an indicator of the status of GSH metabolism in one or more of the major organs, we used a burn rabbit model to determine GSH concentrations and rates of synthesis in WB, liver, lungs, kidney, and skeletal muscle. L-[1-13C]-cysteine was infused intravenously for 6 h in rabbits at 3 days post-burn and in sham burn controls. WB and organ 13C-enrichment of cysteine and GSH was determined by gas chromatography/mass spectrometry. Plasma cysteine metabolic flux was increased significantly (P < 0.01) following burn injury. WB, liver, and lung GSH concentrations (P = 0.054, P < 0.05, and P < 0.05, respectively) and fractional rates of GSH synthesis (P < 0.05, P < 0.01, and P < 0.05, respectively) were reduced at 3 days post-burn. Kidney was unaffected. There also appears to be an increased rate of GSH transport out of the liver after burn injury. Hence, there is a differential impact of burn injury on tissue and organ GSH status, with WB qualitatively reflecting the changes in lung and liver. It will be important to determine whether these changes are due to alterations in the intrinsic capacity for GSH synthesis and/or availability of amino acid precursors of GSH.
User Interface Design Principles for Digital Libraries

Today's digital libraries are extreme complex information systems, which run on the Internet (1). The facili- ties of digital libraries are increasing daily as the technology advances with a motive to provide the appropriate information to its users. The very purpose of the digital libraries is to provide the required information to its users in a convenient and fashioned manner. Since the digital libraries are running on the Internet and the users are from different psychological, educational and social backgrounds, the usage of digital libraries is varying from user to user which entail the need of best user interface. Hence, this paper proposes some design principles for user interfaces for digital libraries for its effective implemen- tation.
The Human Toll Signaling Pathway: Divergence of Nuclear Factor κB and JNK/SAPK Activation Upstream of Tumor Necrosis Factor Receptor–associated Factor 6 (TRAF6)

The human homologue of Drosophila Toll (hToll) is a recently cloned receptor of the interleukin 1 receptor (IL-1R) superfamily, and has been implicated in the activation of adaptive immunity. Signaling by hToll is shown to occur through sequential recruitment of the adapter molecule MyD88 and the IL-1R–associated kinase. Tumor necrosis factor receptor–activated factor 6 (TRAF6) and the nuclear factor κB (NF-κB)–inducing kinase (NIK) are both involved in subsequent steps of NF-κB activation. Conversely, a dominant negative version of TRAF6 failed to block hToll-induced activation of stress-activated protein kinase/c-Jun NH2-terminal kinases, thus suggesting an early divergence of the two pathways.
An Algorithm for Automated Fractal Terrain Deformation

Fractal terrains provide an easy way to generate realistic landscapes. There are several methods to generate fractal terrains, but none of those algorithms allow the user much flexibility in controlling the shape of the final outcome. A few methods to modify fractal terrains have been presented, both algorithm-based as well as by hand editing, but none of these provide a general solution. In this work, we present a new framework for fractal terrain deformation. We provide a general solution that can be applied to a wide variety of deformations. Our approach employs stochastic local search to identify a sequence of local modifications, which deform the fractal terrain to conform to a set of specified constraints. The presented results show that the new method can incorporate multiple constraints simultaneously, while still preserving the natural look of the fractal terrain. We also show how these terrains can be stored efficiently.
Learning to Play Using Low-Complexity Rule-Based Policies: Illustrations through Ms. Pac-Man

In this article we propose a method that can deal with certain combinatorial reinforcement learning tasks. We demonstrate the approach in the popular Ms. Pac-Man game. We define a set of high-level observation and action modules, from which rule-based policies are constructed automatically. In these policies, actions are temporally extended, and may work concurrently. The policy of the agent is encoded by a compact decision list. The components of the list are selected from a large pool of rules, which can be either handcrafted or generated automatically. A suitable selection of rules is learnt by the cross-entropy method, a recent global optimization algorithm that fits our framework smoothly. Cross-entropy-optimized policies perform better than our hand-crafted policy, and reach the score of average human players. We argue that learning is successful mainly because (i) policies may apply concurrent actions and thus the policy space is sufficiently rich, (ii) the search is biased towards low-complexity policies and therefore, solutions with a compact description can be found quickly if they exist.
Problem Solving with Different Models

In this paper a concrete Boolean problem is considered and its solution is represented in three different approaches, as follows: (1) a diagrammatic model of the associated logical circuit, (2) a transitionbased model using Finite State Machine, and (3) an algebraic model for the system specification. The three models are equivalent, in the sense of system behaviour, but they are differently treated as specification and verification supports. As practical dimension, the considerations of this paper start from the behaviour of a logical system and provide an interesting connection with the classical concurrent producer-consumer buffer.
Scalable Link Prediction in Social Networks Based on Local Graph Characteristics

Online social networks (OSNs) like Face book, My space, and Hi5 have become popular, because they allow users to easily share content or expand their social circle. OSNs recommend new friends to registered users based on local graph features (i.e. based on the number of common friends that two users share). However, OSNs do not exploit all different length paths of the network. Instead, they consider only pathways of maximum length 2 between a user and his candidate friends. On the other hand, there are global approaches, which detect the overall path structure in a network, being computationally prohibitive for huge-size social networks. In this paper, we provide friend recommendations, also known as the link prediction problem, by traversing all paths of a bounded length, based on the "algorithmic small world hypothesis. " As a result, we are able to provide more accurate and faster friend recommendations. We perform an extensive experimental comparison of the proposed method against existing link prediction algorithms, using two real data sets (Hi5 and Epinions). Our experimental results show that our Friend Link algorithm outperforms other approaches in terms of effectiveness and efficiency in all data sets. Finally, we discuss extensively various experimental considerations, such as a possible Map Reduce implementation of Friend Link algorithm to achieve scalability.
Pragmatics and Computational Linguistics [ for Handbook of Pragmatics ]

These days there’s a computational version of everything. C omputational biology, computational musicology, computational archaeology, et c, tc. Even movies are going digital. This chapter, as you might have guessed by now , thus explores the computational side of pragmatics. Computational pragmati cs might be defined as the computational study of the relation between utteranc s and context. Like other kinds of pragmatics, this means that computational pr agmatics is concerned with indexicality, with the relation between utterances an d ction, with the relation between utterances and discourse, and with the relationshi p between utterances and the place, time, and environmental context of their being ut tered. As Bunt and Black (2000) point out, computational pragmatic s, like pragmatics in general, is especially concerned with inference. Four core inferential problems in pragmatics have received the most attention in the comput ational community: reference resolution , the interpretation and generation of speech acts , the interpretation and generation of discourse structure , and the problem of abduction. Each of these four problems can be cast as an inference task, one of so mehow filling in information that isn’t actually present in the utterance at ha nd. Two of these tasks are addressed in other chapters of this volume; abduction in Cha pter X, and discourse structure and coherence in Chapter Y. I have therefore chose n the interpretation of speech acts as the topic of this chapter. Speech act interpretation, a classic pragmatic problem, is a good choice for this overview chapter for many reasons. First, the early com putational work drew very strongly from the linguistic literature of the period. This enables us to closely compare the ways that computational linguistic and non-com putational linguistic approaches differ in their methodology Second, there are tw o distinct computational paradigms in speech act interpretation: a logic-bas ed approach and a probabilistic approach. I see these two approaches as good vehic les for motivating the
Uniform Consensus is Harder than Consensus ( extended abstract )

We compare the consensus problem with the uniform consensus problem in synchronous systems. In contrast to consensus, uniform consensus is not solvable in synchronous systems with byzantine failures. This still holds for the omission failure model if a majority of processes may be faulty. For the crash failure model, both consensus and uniform consensus are solvable, no matter how many processes are faulty. We consider this failure model and we examine the number of rounds required to reach a decision in consensus and uniform consensus algorithms. We show that compared with the best consensus algorithm, any uniform consensus algorithm takes at least one additional round to take a decision. We thus prove that uniform consensus is also harder than consensus whatever the failure model is.
Coevolving the "Ideal" Trainer: Application to the Discovery of Cellular Automata Rules

Coevolution provides a framework to implement search heuristics that are more elaborate than those driving the exploration of the state space in canonical evolutionary systems. However, some drawbacks have also to be overcome in order to ensure continuous progress on the long term. This paper presents the concept of coevolutionary learning and introduces a search procedure which successfully addresses the underlying impediments in coevolutionary search. The application of this algorithm to the discovery of cellular automata rules for a classi cation task is described. This work resulted in a signi cant improvement over previously known best rules for this task.
Reverse geocoding for photo captioning with a meta-gazetteer

Gazetteers play an essential role in GIS in translating between place name and coordinate-based descriptions of location. The proliferation of location-aware social media applications has led to new sources of gazetteer data, many of which are crowd-sourced. They complement the conventional authoritative resources that are typically linked to published map products. We illustrate the variation in performance of several, mostly social media based, gazetteer resources for a reverse-geocoding photo captioning task and demonstrate the advantage of a meta-gazetteer service that integrates multiple individual gazetteer resources and employs several toponym ranking methods.
Bond strength of orthodontic brackets using different light and self-curing cements.

The purpose of the study was to evaluate the shear bond strength of stainless steel orthodontic brackets directly bonded to extracted human premolar teeth. Fifty teeth were randomly divided into five groups: (1) System One (chemically cured composite resin), (2) Light Bond (light-cured composite resin), (3) Vivaglass Cem (self-curing glass ionomer cement), (4) Fuji Ortho LC (light-cured glass ionomer cement) used after 37% orthophosphoric acid-etching of enamel (5) Fuji Ortho LC without orthophosphoric acid-etching. The brackets were placed on the buccal and lingual surfaces of each tooth, and the specimens were stored in distilled water (24 hours) at 37 degrees C and thermocycled. Teeth were mounted on acrylic block frames, and brackets were debonded using an Instron machine. Shear bond strength values at fracture (Nw) were recorded. ANOVA and Student-Newman-Keuls multiple comparison tests were performed (P < .05). Bonding failure site was recorded by stereomicroscope and analyzed by Chi-square test, selected specimens of each group were observed by scanning electron microscope. System One attained the highest bond strength. Light Bond and Fuji Ortho LC, when using an acid-etching technique, obtained bond strengths that were within the range of estimated bond strength values for successful clinical bonding. Fuji Ortho LC and Vivaglass Cem left an almost clean enamel surface after debracketing.
‘Squaring’ is Better at Predicting Plaid Motion than the Vector Average or Intersection of Constraints

How do humans combine the velocity information from two moving gratings (plaids) to detect pattern motion direction? We are still unable to answer this question. The ‘intersection of constraints’ rule (IOC—Adelson and Movshon, 1982 Nature 300 523–525), and the ‘vector average’ rule (VA—Wilson et al, 1992 Visual Neuroscience 9 79–97) have both been supported by results in the plaid literature, but could these results be predicted by a ‘squaring’ nonlinearity that now forms part of several influential spatiotemporal energy models (Wilson et al 1992, loco cit.; Lu and Sperling, 1995 Vision Research 35 2697–2722; Simoncelli and Heeger, 1998 Vision Research 38 743–761)? Spatiotemporal energy in these models predicts directions other than those predicted by standard spatiotemporal energy models and may underlie the results that support the combination rules. The two combination rules and predictions from ‘squaring’ were tested under identical conditions. In the first three experiments a plaid was randomly presented in one of 45 different orientations, and observers were asked to remember the direction. The stimulus was then replaced by an oriented line indicating the direction predicted by one of the hypotheses. The observer was unaware which hypothesis had generated the line and was asked to make a same/different judgment. Results showed that the ‘squaring’ hypothesis was better at predicting perceived direction than either the IOC or VA.
Fantasy Sport, FoMO, and Traditional Fandom: How Second-Screen Use of Social Media Allows Fans to Accommodate Multiple Identities

Fantasy sport has become a prominent topic of study for sport management scholars over the last decade, and along with the rise of this research have come questions regarding how fantasy sport involvement impacts fans’ loyalty to their favorite team(s). Although this question has been posed several times, results have been mixed. We posit that this is largely attributable to the fact that to this point researchers have not considered the situational environment under which fantasy sport has proliferated or the psychological processes of consumers facing multiple consumption options. Therefore, we examined a model featuring fear of missing out as an antecedent to fantasy sport involvement, social media involvement, and team identity salience during games. Furthermore, we examine the role social media involvement plays in allowing fans to accommodate both their fantasy sport and team identities during games. Theoretical and practical implications are discussed.
Energy-Aware Set-Covering Approaches for Approximate Data Collection in Wireless Sensor Networks

To conserve energy, sensor nodes with similar readings can be grouped such that readings from only the representative nodes within the groups need to be reported. However, efficiently identifying sensor groups and their representative nodes is a very challenging task. In this paper, we propose a centralized algorithm to determine a set of representative nodes with high energy levels and wide data coverage ranges. Here, the data coverage range of a sensor node is considered to be the set of sensor nodes that have reading behaviors very close to the particular sensor node. To further reduce the extra cost incurred in messages for selection of representative nodes, a distributed algorithm is developed. Furthermore, maintenance mechanisms are proposed to dynamically select alternative representative nodes when the original representative nodes run low on energy, or cannot capture spatial correlation within their respective data coverage ranges. Using experimental studies on both synthesis and real data sets, our proposed algorithms are shown to effectively and efficiently provide approximate data collection while prolonging the network lifetime.
CUgrep: A GPU-based high performance multi-string matching system

String matching is one of the oldest and most pervasive problems in computer science. Nowadays applications related to string matching can be found everywhere. Meanwhile, the heterogeneous processing of CPU+GPU has become the popular parallel platform in solving high performance computing applications. This paper proposes a GPU-based multi-string matching algorithm, CUgrep, and uses this algorithm to implement the webpage matching system, which is almost 40 times peak performance to the original BNDM algorithm used in Nrgrep1.
An adaptive paging area selection scheme

The pressure of low costs and high capacity has pushed the network operation and management into the era of requiring the self-planning, self-configuration, and self-optimization of the networks. Many solutions used in the legacy planning, installation, and operation are therefore insufficient to meet the challenges. New approaches of network operation and management are thus needed, which make the optimum decisions and take the actions automatically. Paging is a key function of most radio access networks. For the paging to work in the "self" manner, the networks need an automatic approach to determine the optimum paging areas in the new era. This work therefore contributes with an adaptive paging area selection scheme. The simulation experiment shows the proposed scheme works automatically and provides significant improvement with its optimum decision.
Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples

Although a few hundred single nucleotide polymorphisms (SNPs) suffice to infer close familial relationships, high density genome-wide SNP data make possible the inference of more distant relationships such as 2nd to 9th cousinships. In order to characterize the relationship between genetic similarity and degree of kinship given a timeframe of 100–300 years, we analyzed the sharing of DNA inferred to be identical by descent (IBD) in a subset of individuals from the 23andMe customer database (n = 22,757) and from the Human Genome Diversity Panel (HGDP-CEPH, n = 952). With data from 121 populations, we show that the average amount of DNA shared IBD in most ethnolinguistically-defined populations, for example Native American groups, Finns and Ashkenazi Jews, differs from continentally-defined populations by several orders of magnitude. Via extensive pedigree-based simulations, we determined bounds for predicted degrees of relationship given the amount of genomic IBD sharing in both endogamous and ‘unrelated’ population samples. Using these bounds as a guide, we detected tens of thousands of 2nd to 9th degree cousin pairs within a heterogenous set of 5,000 Europeans. The ubiquity of distant relatives, detected via IBD segments, in both ethnolinguistic populations and in large ‘unrelated’ populations samples has important implications for genetic genealogy, forensics and genotype/phenotype mapping studies.
Linking patterns and processes across scales: the application of scale-transition theory to algal dynamics on rocky shores

SUMMARY Understanding how species and environments respond to global anthropogenic disturbances is one of the greatest challenges for contemporary ecology. The ability to integrate modeling, correlative and experimental approaches within individual research programs will be key to address large-scale, long-term environmental problems. Scale-transition theory (STT) enables this level of integration, providing a powerful framework to link ecological patterns and processes across spatial and temporal scales. STT predicts the large-scale (e.g. regional) behavior of a system on the basis of nonlinear population models describing local (e.g. patch-scale) dynamics and the interaction between these nonlinearities and spatial variation in population abundance or environmental conditions. Here we use STT to predict the dynamics of turf-forming algae on rocky shores at Capraia Island, in the northwest Mediterranean. We developed a model of algal turf dynamics based on density-dependent growth that included the effects of local interactions with canopy algae. The model was parameterized with field data and used to scale up the dynamics of algal turfs from the plot scale (20×20 cm) to the island scale (tens of km). The interaction between nonlinear growth and spatial variance in cover of turfing algae emerged as a key term to translate the local dynamics up to the island scale. The model successfully predicted short-term and long-term mean values of turf cover estimated independently from a separate experiment. These results illustrate how STT can be used to identify the relevant mechanisms that drive large-scale changes in ecological communities. We argue that STT can contribute significantly to the connection between biomechanics and ecology, a synthesis that is at the core of the emerging field of ecomechanics.
Death by small forces: a fracture and fatigue analysis of wave-swept macroalgae

SUMMARY Wave-swept macroalgae are subjected to large hydrodynamic forces as each wave breaks on shore, loads that are repeated thousands of times per day. Previous studies have shown that macroalgae can easily withstand isolated impositions of maximal field forces. Nonetheless, macroalgae break frequently. Here we investigate the possibility that repeated loading by sub-lethal forces can eventually cause fracture by fatigue. We determine fracture toughness, in the form of critical strain energy release rate, for several flat-bladed macroalgae, thereby assessing their resistance to complete fracture in the presence of cracks. Critical energy release rates are evaluated through single-edge-notch, pull-to-break tests and single-edge-notch, repeated-loading tests. Crack growth at sub-critical energy release rates is measured in repeated-loading tests, providing a first assessment of algal breakage under conditions of repeated loading. We then estimate the number of imposed waves required for un-notched algal blades to reach the point of complete fracture. We find that, if not checked by repair, fatigue crack growth from repeated sub-lethal stresses may completely fracture individuals within days. Our results suggest that fatigue may play an important role in macroalgal breakage.