Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximation Algorithms for Min-Max Cycle Cover Problems

As a fundamental optimization problem, the vehicle routing problem has wide application backgrounds and has been paid lots of attentions in past decades. In this paper we study its applications in data gathering and wireless energy charging for wireless sensor networks, by devising improved approximation algorithms for it and its variants. The key ingredients in the algorithm design include exploiting the combinatorial properties of the problems and making use of tree decomposition and minimum weighted maximum matching techniques. Specifically, given a metric complete graph G and an integer k > 0, we consider rootless, uncapacitated rooted, and capacitated rooted min-max cycle cover problems in G with an aim to find k rootless (or rooted) edge-disjoint cycles covering the vertices in V such that the maximum cycle weight among the k cycles is minimized. For each of the mentioned problems, we develop an improved approximate solution. That is, for the rootless min-max cycle cover problem, we develop a (531+ ε)-approximation algorithm; for the uncapacitated rooted min-max cycle cover problem, we devise a (631+ ε)-approximation algorithm; and for the capacitated rooted min-max cycle cover problem, we propose a (7 + ε)-approximation algorithm. These algorithms improve the best existing approximation ratios of the corresponding problems 6 + ε, 7 + ε, and 13 + ε, respectively, where ε is a constant with 0 <; ε <; 1. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results show that the actual approximation ratios delivered by the proposed algorithms are always no more than 2, much better than their analytical counterparts.
Regulation of macrophage functions by L-arginine

Sites of inflammation with prominent macrophage infiltration, such as wounds and certain tumors, are uniquely deficient in free arginine. The effects of arginine availability on macrophage physiology were investigated. When cultured in media containing less than 0.1 mM L- arginine, rat resident peritoneal macrophages exhibited enhanced spreading, tumor cytotoxicity, superoxide production, phagocytosis, and protein synthesis. Thus, arginine concentrations similar to those found in sites of inflammation can augment macrophage functions, while those found in plasma (approximately 0.1 mM) and in commonly used culture media (0.4 to 1.2 mM) are inhibitory. Culture in homoarginine, but not D-arginine, ornithine, citrulline, urea, histidine, or lysine also inhibited macrophage tumor cytotoxicity, indicating the specificity of the effect. In contrast to resident macrophages, the tumor cytotoxicity of peritoneal macrophages obtained after C. parvum injection was suppressed by culture in arginine-deficient media. However, L-arginine- deficient media enhanced all other activation-associated functions in C. parvum-elicited macrophages as in resident cells. Arginine-free wound fluid promoted resident macrophage tumoricidal activity when compared with rat serum, and again, the addition of L-arginine was inhibitory. The marked effects of L-arginine availability on macrophage functions, together with the knowledge that these cells modify the extracellular arginine concentration in sites of inflammation through arginase, provide evidence for an autoregulatory mechanism of macrophage activation.
Preclinical Evaluation of a Replication-Deficient Intranasal ΔNS1 H5N1 Influenza Vaccine

Background We developed a novel intranasal influenza vaccine approach that is based on the construction of replication-deficient vaccine viruses that lack the entire NS1 gene (ΔNS1 virus). We previously showed that these viruses undergo abortive replication in the respiratory tract of animals. The local release of type I interferons and other cytokines and chemokines in the upper respiratory tract may have a “self-adjuvant effect”, in turn increasing vaccine immunogenicity. As a result, ΔNS1 viruses elicit strong B- and T- cell mediated immune responses. Methodology/Principal Findings We applied this technology to the development of a pandemic H5N1 vaccine candidate. The vaccine virus was constructed by reverse genetics in Vero cells, as a 5∶3 reassortant, encoding four proteins HA, NA, M1, and M2 of the A/Vietnam/1203/04 virus while the remaining genes were derived from IVR-116. The HA cleavage site was modified in a trypsin dependent manner, serving as the second attenuation factor in addition to the deleted NS1 gene. The vaccine candidate was able to grow in the Vero cells that were cultivated in a serum free medium to titers exceeding 8 log10 TCID50/ml. The vaccine virus was replication deficient in interferon competent cells and did not lead to viral shedding in the vaccinated animals. The studies performed in three animal models confirmed the safety and immunogenicity of the vaccine. Intranasal immunization protected ferrets and mice from being infected with influenza H5 viruses of different clades. In a primate model (Macaca mulatta), one dose of vaccine delivered intranasally was sufficient for the induction of antibodies against homologous A/Vietnam/1203/04 and heterologous A/Indonesia/5/05 H5N1 strains. Conclusion/Significance Our findings show that intranasal immunization with the replication deficient H5N1 ΔNS1 vaccine candidate is sufficient to induce a protective immune response against H5N1 viruses. This approach might be attractive as an alternative to conventional influenza vaccines. Clinical evaluation of ΔNS1 pandemic and seasonal influenza vaccine candidates are currently in progress.
A wireless sensor network routing protocol for fire estimation in building

As the most appropriate data processing method of Ambient Intelligence, wireless sensor network has a broad space of application. One of the most important applications of wireless sensor network is fire rescuing in building, and there are many special technology requirement for this application. In order to resolve nodes uneven distribution and exactly estimation the location and intensity of fire, a target oriented distribution routing protocol based on LEACH, which is called LEACH-TOD, is proposed. LEACH-TOD improves the cluster heads selecting process of traditional LEACH protocol, and offsets the defects of LEACH protocol on rationality of cluster heads position and communication quality in cluster in the uneven nodes distribution. The proper clustering structure is formed through node density measuring analyze and threshold limitation to provide effective and rational routing structure for information collecting. The experiments prove that the LEACH-TOD protocol prolongs the whole lifetime of the network and serves to the accuracy of fire field parameter model foundation.
SCHEDULING ISSUES IN REAL TIME SYSTEMS FOR INDUSTRIAL NETWORK

One aspect to investigate in the attempt to enhance the support of process control traffic is the local transmission scheduling algorithm used to queue the requests. In the factory automation the correctness of many systems and devices depends not only on the effects of results they produce, but also on the time at which these results are produced. This paper presents one deadline aware scheduling approach to transmit real-time periodic and aperiodic requests and non-real-time requests.
N-acetylcysteine attenuates progression of liver pathology in a rat model of nonalcoholic steatohepatitis.

A "2-hit" model for nonalcoholic steatohepatitis (NASH) has been proposed in which steatosis constitutes the "first hit" and sensitizes the liver to potential "second hits" resulting in NASH. Oxidative stress is considered a candidate for the second hit. N-acetylcysteine (NAC), an antioxidant, has been suggested as a dietary therapy for NASH. We examined the effects of NAC in a rat total enteral nutrition (TEN) model where NASH develops as the result of overfeeding dietary polyunsaturated fat. Male Sprague-Dawley rats consumed pelleted AIN-93G diets ad libitum or were overfed a 9200 kJ.kg(-0.75). d(-1) liquid diet containing 70% corn oil with or without 2 g.kg(-1). d(-1) NAC i.g. for 65 d. Hepatic steatosis was not influenced by dietary supplementation with NAC; however, the liver pathology score was lower (P </= 0.05) and NAC provided partial protection against alanine aminotransferase release (P </= 0.05). NAC attenuated increased hepatic oxidative stress (TBARS; P </= 0.05) and prevented increases in cytochrome P450 2E1 apoprotein and mRNA and in tumor necrosis factor-alpha (TNFalpha) mRNA. Titers of auto-antibodies against proteins adducted to lipid peroxidation products were lower in serum of the NAC group than in the 70% corn oil group (P </= 0.05). NAC also decreased Picosirius red staining of collagen, a marker of fibrosis. However, markers of hepatic stellate cell activation were unaffected. Using NAC in a TEN model of NASH, we have demonstrated that NAC prevents many aspects of NASH progression by decreasing development of oxidative stress and subsequent increases in TNFalpha but does not block development of steatosis.
Hardware implementation of the GPS authentication

In this paper, we explore new area/throughput tradeoffs for the Girault, Poupard and Stern authentication protocol (GPS). This authentication protocol was selected in the NESSIE competition and is even part of the standard ISO/IEC 9798. The originality of our work comes from the fact that we exploit a fixed key to increase the throughput. It leads us to implement GPS using the Chapman constant multiplier. This parallel implementation is 40 times faster but 10 times bigger than the reference serial one. We propose to serialize this multiplier to reduce its area at the cost of lower throughput. Our hybrid Chapman's multiplier is 8 times faster but only twice bigger than the reference. Results presented here allow designers to adapt the performance of GPS authentication to their hardware resources. The complete GPS prover side is also integrated in the network stack of the PowWow sensor which contains an Actel IGLOO AGL250 FPGA as a proof of concept.
Wavelet-constrained stereo matching under photometric variations

We propose a new method to address the problem of stereo matching under varying illumination conditions. First, a spatially varying multiplicative model is developed to account for photometric changes induced between both images in the stereo pair. The stereo matching problem based on this model is then formulated as a constrained optimization problem in which an appropriate convex objective function is minimized under convex constraints. These constraints arise from prior knowledge and rely on various properties of both disparity and illumination fields. In order to obtain a smooth disparity field while preserving discontinuities around object edges, we consider an appropriate wavelet-based regularization constraint. The resulting multi-constrained optimization problem is solved via an efficient block iterative algorithm which offers great flexibility in the incorporation of several constraints. Experimental results demonstrate the efficiency of the proposed method to recover illumination changes and disparity map simultaneously, making stereo matching very robust w.r. t. such changes.
UNIBA: Combining Distributional Semantic Models and Sense Distribution for Multilingual All-Words Sense Disambiguation and Entity Linking

This paper describes the participation of the UNIBA team in the Task 13 of SemEval-2015 about Multilingual All-Words Sense Disambiguation and Entity Linking. We propose an algorithm able to disambiguate both word senses and named entities by combining the simple Lesk approach with information coming from both a distributional semantic model and usage frequency of meanings. The results for both English and Italian show satisfactory performance.
A model of structured discourse for cooperating intelligent agents

Resolution of large problems in an organizational context often requires decomposition of the problem into subproblems which will allow individual agents to work on the subproblem of their expertise and resolve the overall problem through coordination with each other. Examples of such problems include engineering and software design, project planning, product design and marketing, and auditing decisions. We address the issue of designing information sharing and cooperation mechanisms to support intelligent agents in the overall problem resolution process using distributed AI techniques. The central mechanism that renders the subproblems to be relatively independent is the truth maintenance system at the individual agent (intra-agent) level which allows a consistent integration of observations, assumptions, and rules to arrive at propositions regarding a subproblem and allows the member to maintain a non-conflicting set of beliefs. We propose a discourse protocol which allows agents to communicate in a structured fashion and an inter-agent truth maintenance system which allows multiple agents to identify conflicting beliefs. A conflict resolution strategy allows agents to resolve both internal conflicts and most inter-agent conflicts. We illustrate the working of the model and discuss the design of a prototype system.
Reconstruction of the Masticatory Apparatus of the Holotype of the Rhynchosaur Hyperodapedon sanjuanensis from the Late Triassic of Argentina: Implications for the Diagnosis of the Species

Abstract. Rhynchosaurs are a clade of robust, quadruped, and herbivorous stem-archosauromorph diapsids restricted to the Triassic Period. Most species have a specialized masticatory apparatus composed of a blade-and-groove occlusion and multiple longitudinal tooth rows. Rhynchosaurs are the most numerically abundant tetrapods of the Upper Triassic Ischigualasto Formation of NW Argentina. However, there is currently a single nominal species, Hyperodapedon sanjuanensis, described for this unit and the entire country. Though the dental morphology constitutes one of the most important sources of taxonomic and phylogenetic information of the group, this anatomical region remains undescribed in the holotype of Hyperodapedon sanjuanensis. The full occlusion of the skull and lower jaw obscures most of the morphology of the masticatory apparatus in this specimen. Here we present the first description of the maxillary tooth plate and dentary dentition of this specimen based on CT scan data and a three-dimensional rendering. The maxillary tooth plate of the holotype of Hyperodapedon sanjuanensis possesses two tooth-bearing areas that are separated by a single longitudinal groove. The lateral tooth-bearing area of the maxilla is wider than the medial one. The dentary possesses a single cutting blade and tooth row. Both maxilla and dentary lack lingual dentition. The information gathered here was used to emend the diagnosis of the species, review the taxonomy of some specimens, and check the dental scorings for Hyperodapedon sanjuanensis—based on the morphology of the holotype—in three independent phylogenetic data sets.
Binary classification performances of emotion classes for Turkish Emotional Speech

Emotion recognition from speech plays important role for natural human-computer interaction. This study investigates binary classification performances of 4 fundamental emotion classes in Turkish Emotional Speech (TurES) Database using acoustic features for various classifiers. Results shows that Angry emotion class has higher classification rate (70%-80%) than others; lowest classification rate is obtained as 64% for Happy-Neutral emotion pair. Best classification results are obtained with J48 (C4.5) classifier for all emotion pairs.
Parameter-Free Spectral Kernel Learning

Due to the growing ubiquity of unlabeled data, learning with unlabeled data is attracting increasing attention in machine learning. In this paper, we propose a novel semi-supervised kernel learning method which can seamlessly combine manifold structure of unlabeled data and Regularized Least-Squares (RLS) to learn a new kernel. Interestingly, the new kernel matrix can be obtained analytically with the use of spectral decomposition of graph Laplacian matrix. Hence, the proposed algorithm does not require any numerical optimization solvers. Moreover, by maximizing kernel target alignment on labeled data, we can also learn model parameters automatically with a closed-form solution. For a given graph Laplacian matrix, our proposed method does not need to tune any model parameter including the tradeoff parameter in RLS and the balance parameter for unlabeled data. Extensive experiments on ten benchmark datasets show that our proposed two-stage parameter-free spectral kernel learning algorithm can obtain comparable performance with fine-tuned manifold regularization methods in transductive setting, and outperform multiple kernel learning in supervised setting.
Structured and incoherent parametric dictionary design

A new dictionary selection approach for sparse coding, called parametric dictionary design, has recently been introduced. The aim is to choose a dictionary from a class of admissible dictionaries which can be presented parametrically. The designed dictionary satisfies a constraint, here the incoherence property, which can help conventional sparse coding methods to find sparser solutions in average. In this paper, an extra constraint will be applied on the parametric dictionaries to find a structured dictionary. Various structures can be imposed on dictionaries to promote a correlation between the atoms. We intentionally choose a structure to implement the dictionary using a set of filter banks. This indeed helps to implement the dictionary-signal multiplications more efficiently. The price we pay for the extra structure is that the designed dictionary is not as incoherent as unstructured parametric designed dictionaries.
Misuse of the Mood Disorders Questionnaire as a case-finding measure and a critique of the concept of using a screening scale for bipolar disorder in psychiatric practice.

OBJECTIVES Under-recognition of bipolar disorder (BD) is common and incurs significant costs for individuals and society. Clinicians are often encouraged to use screening instruments to help them identify patients with the disorder. The Mood Disorder Questionnaire (MDQ) is the most widely studied measure for this purpose. Some studies, however, have used the MDQ as a case-finding instrument rather than a screening scale. Such inappropriate use of screening scales risks distorting perceptions about many facets of BD, from its prevalence to its consequences. METHODS Studies using the MDQ were reviewed to identify those reports that have used the scale as a case-finding measure rather than a screening scale. RESULTS Multiple studies were identified in the BD literature that used the MDQ as a diagnostic proxy. The findings of these studies were misinterpreted because of the failure to make the distinction between screening and case-finding. CONCLUSIONS Inappropriate conclusions have been drawn regarding the prevalence, morbidity, and diagnostic under-recognition of BD in studies that rely on the MDQ as a diagnostic proxy. A conceptual critique is offered against the use of self-administered screening questionnaires for the detection of BD in psychiatric settings.
A New Source of Data for Public Health Surveillance: Facebook Likes

Background Investigation into personal health has become focused on conditions at an increasingly local level, while response rates have declined and complicated the process of collecting data at an individual level. Simultaneously, social media data have exploded in availability and have been shown to correlate with the prevalence of certain health conditions. Objective Facebook likes may be a source of digital data that can complement traditional public health surveillance systems and provide data at a local level. We explored the use of Facebook likes as potential predictors of health outcomes and their behavioral determinants. Methods We performed principal components and regression analyses to examine the predictive qualities of Facebook likes with regard to mortality, diseases, and lifestyle behaviors in 214 counties across the United States and 61 of 67 counties in Florida. These results were compared with those obtainable from a demographic model. Health data were obtained from both the 2010 and 2011 Behavioral Risk Factor Surveillance System (BRFSS) and mortality data were obtained from the National Vital Statistics System. Results Facebook likes added significant value in predicting most examined health outcomes and behaviors even when controlling for age, race, and socioeconomic status, with model fit improvements (adjusted R 2) of an average of 58% across models for 13 different health-related metrics over basic sociodemographic models. Small area data were not available in sufficient abundance to test the accuracy of the model in estimating health conditions in less populated markets, but initial analysis using data from Florida showed a strong model fit for obesity data (adjusted R 2=.77). Conclusions Facebook likes provide estimates for examined health outcomes and health behaviors that are comparable to those obtained from the BRFSS. Online sources may provide more reliable, timely, and cost-effective county-level data than that obtainable from traditional public health surveillance systems as well as serve as an adjunct to those systems.
Tidally distorted accretion discs in binary stars

The non-axisymmetric features observed in the discs of dwarf novae in outburst are usually considered to be spiral shocks, which are the non-linear relatives of tidally excited waves. This interpretation suffers from a number of problems. For example, the natural site of wave excitation lies outside the Roche lobe, the disc must be especially hot, and most treatments of wave propagation do not take into account the vertical structure of the disc. In this paper I construct a detailed semi-analytical model of the non-linear tidal distortion of a thin, three-dimensional accretion disc by a binary companion on a circular orbit. The analysis presented here allows for vertical motion and radiative energy transport, and introduces a simple model for the turbulent magnetic stress. The m=2 inner vertical resonance has an important influence on the amplitude and phase of the tidal distortion. I show that the observed patterns find a natural explanation if the emission is associated with the tidally thickened sectors of the outer disc, which may be irradiated from the centre. According to this hypothesis, it may be possible to constrain the physical parameters of the disc through future observations.
Hormonal networks involved in apical hook development in darkness and their response to light

In darkness, the dicot seedlings produce an apical hook as result of differential cell division and extension at opposite sides of the hypocotyl. This hook protects the apical meristem from mechanical damage during seedling emergence from the soil. In darkness, gibberellins act via the DELLA-PIF (PHYTOCHROME INTERACTING FACTORs) pathway, and ethylene acts via the EIN3/EIL1 (ETHYLENE INSENSITIVE 3/EIN3 like 1)-HLS1 (HOOKLESS 1) pathway to control the asymmetric accumulation of auxin required for apical hook formation and maintenance. These core pathways form a network with multiple points of connection. Light perception by phytochromes and cryptochromes reduces the activity of PIFs and (COP1) CONSTITUTIVE PHOTOMORPHOGENIC 1—both required for hook formation in darkness—, lowers the levels of gibberellins, and triggers hook opening as a component of the switch between heterotrophic and photoautotrophic development. Apical hook opening is thus a suitable model to study the convergence of endogenous and exogenous signals on the control of cell division and cell growth.