Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Monitoring of Photocytotoxicity in Nanoparticles-Based Photodynamic Therapy: A Model-Based Approach

Nanoparticles are widely suggested as targeted drug-delivery systems. In photodynamic therapy (PDT), the use of multifunctional nanoparticles as photoactivatable drug carriers is a promising approach for improving treatment efficiency and selectivity. However, the conventional cytotoxicity assays are not well adapted to characterize nanoparticles cytotoxic effects and to discriminate early and late cell responses. In this work, we evaluated a real-time label-free cell analysis system as a tool to investigate in vitro cyto- and photocyto-toxicity of nanoparticles-based photosensitizers compared with classical metabolic assays. To do so, we introduced a dynamic approach based on real-time cell impedance monitoring and a mathematical model-based analysis to characterize the measured dynamic cell response. Analysis of real-time cell responses requires indeed new modeling approaches able to describe suited use of dynamic models. In a first step, a multivariate analysis of variance associated with a canonical analysis of the obtained normalized cell index (NCI) values allowed us to identify different relevant time periods following nanoparticles exposure. After light irradiation, we evidenced discriminant profiles of cell index (CI) kinetics in a concentration- and light dose-dependent manner. In a second step, we proposed a full factorial design of experiments associated with a mixed effect kinetic model of the CI time responses. The estimated model parameters led to a new characterization of the dynamic cell responses such as the magnitude and the time constant of the transient phase in response to the photo-induced dynamic effects. These parameters allowed us to characterize totally the in vitro photodynamic response according to nanoparticle-grafted photosensitizer concentration and light dose. They also let us estimate the strength of the synergic photodynamic effect. This dynamic approach based on statistical modeling furnishes new insights for in vitro characterization of nanoparticles-mediated effects on cell proliferation with or without light irradiation.
Issue competition and presidential debates in multiparty systems: evidence from the 2002, 2007, and 2012 Korean presidential elections

ABSTRACT Which issues do political parties emphasize in campaigns? Selecting the issues to emphasize in campaigns is treated with the same importance as policy positioning. Nevertheless, little attention has been paid to understanding parties’ strategies of issue competition in presidential elections under multiparty systems. By analyzing statements of presidential candidates in the 2002, 2007, and 2012 Korean presidential debates, we find that presidential candidates use their issue emphasis strategies differently in presidential elections according to party size and ideological relationships with other parties. Specifically, a small party’s candidates have been more likely than mainstream parties’ candidates to pursue their issue ownership advantage. In addition, a mainstream party’s candidates have emphasized the issues of a small party more than those of his own party when the two parties have had a similar ideological foundation, whereas, when there were no such ideological similarities, a mainstream party’s candidate has only focused on issues of the mainstream party. Our results imply that the political communication used by political parties and candidates is conditioned not only by political contexts such as electoral systems or party systems but also by the size and ideology of parties.
Describing ancient horizontal gene transfers at the nucleotide and gene levels by comparative pathogenicity island genometrics

MOTIVATION Lateral gene transfer is a major mechanism contributing to bacterial genome dynamics and pathovar emergence via pathogenicity island (PAI) spreading. However, since few of these genomic exchanges are experimentally reproducible, it is difficult to establish evolutionary scenarios for the successive PAI transmissions between bacterial genera. Methods initially developed at the gene and/or nucleotide level for genomics, i.e. comparisons of concatenated sequences, ortholog frequency, gene order or dinucleotide usage, were combined and applied here to homologous PAIs: we call this approach comparative PAI genometrics. RESULTS YAPI, a Yersinia PAI, and related islands were compared with measure evolutionary relationships between related modules. Through use of our genometric approach designed for tracking codon usage adaptation and gene phylogeny, an ancient inter-genus PAI transfer was oriented for the first time by characterizing the genomic environment in which the ancestral island emerged and its subsequent transfers to other bacterial genera.
Spike Synchronization Dynamics of Small-World Networks

In this research report, we examine the effects of small-world network organization on spike synchronization dynamics in networks of Izhikevich spiking units. We interpolate network organizations from regular ring lattices, through the small-world region, to random networks, and measure global spike synchronization dynamics. We examine how average path length and clustering effect the dynamics of global and neighborhood clique spike organization and propagation. We show that the emergence of global synchronization undergoes a phase transition in the small-world region, between the clustering and path length phase transitions that are known to exist. We add additional realistic constraints on the dynamics by introducing propagation delays of spiking signals proportional to wiring length. The addition of delays interferes with the ability of random networks to sustain global synchronization, in relation to the breakdown of clustering in the networks. The addition of delays further enhances the finding that small-world organization is beneficial for balancing neighborhood synchronized waves of organization with global synchronization dynamics.
Contourlet based feature extraction and classification for Wireless Capsule Endoscopic images

Wireless Capsule Endoscopy (WCE) is a late-model non-invasive device to detect abnormalities in small intestine. The traditional diagnostic method that only depending on clinicians' naked eyes is time-consuming and labor-intensive. It is necessary to develop a computer-aided system to alleviate the burden of clinicians. In this paper, a new color-texture feature extraction method is proposed for the classification of normal and abnormal WCE tissue images. The Contourlet Transform is introduced and used for each color channel of each WCE image in HSV color space. Finally, we construct a 288-dimensions feature vector by calculating the 3-order color moments for each baseband generated by using the Contourlet Transform. Real experiments using different classifiers in various color spaces are implemented to evaluate the performance of the proposed method.
Substructures and density profiles of clusters in models of galaxy formation

In this paper we investigate, using high resolution N-body simulations, the density profiles and the morphologies of galaxy clusters in seven models of structure formation. We show that these properties of clusters are closely related to the occurrence of a significant merging event in the recent past. The seven models are: (1) the standard CDM model (SCDM) with $\Omega_0 = 1$, $\Lambda_0=0$ and $h=0.5$; (2) a low-density flat model (FL03) with $\Omega_0=0.3$, $\Lambda_0=0.7$ and $h=0.75$; (3) an open model (OP03) with $\Omega_0=0.3$, $\Lambda_0=0$ and $h=0.75$; (4) a low-density flat model (FL02) with $\Omega_0=0.2$, $\Lambda_0=0.8$ and $h=1$; (5) an open model (OP02) with $\Omega_0=0.2$, $\Lambda_0=0$ and $h=1$; (6) a low-density flat model (FL01) with $\Omega_0=0.1$ and $\Lambda_0=0.9$; (7) an open model (OP01) with $\Omega_0=0.1$ and $\Lambda_0=0$. We find that the density profiles and morphologies of clusters depend both on $\Omega_0$ and on $\Lambda_0$. For $\Lambda_0=0$, these properties are a monotonic function of $\Omega_0$. Clusters in OP01 have the steepest density profiles, their density contours are the roundest and show the smallest center shifts. The other extreme case is SCDM, where clusters show the least steep density profiles and the most elongated contours. For a given $\Omega_0$ ($<1$), clusters in the flat model (i.e. with $\Lambda_0=1-\Omega_0$) have flatter density profiles and less substructures than in the corresponding open model. In particular, our results show that low-density flat models with $\Omega_0\sim 0.3$, which are currently considered as a successful alternative to SCDM, can produce a substantial fraction of clusters with substructures. This is in contrast to the conception that this kind of models may have serious problem in this aspect.
Explorations in Language Learning by Integrating Analogy and Probability

We present a new approach to language learning which is based on the following idea: if a language learner does not know which phrase-structure trees should be assigned to initial sentences, s/he allows (implicitly) for all possible trees and lets linguistic experience decide which is the ‘best’ tree for each sentence. The best tree is obtained by maximizing ‘structural analogy’ between a sentence and previous sentences, which can be formalized by the most probable shortest combination of subtrees from all trees of previous sentences. It is shown that this model can learn both exemplar-based and rule-based aspects of language, ranging from constructions and phrasal verbs to auxiliary fronting. We support our theoretical results by corpus-based experiments on the Penn Treebank and the CHILDES database. Our model suggests a rapprochement between nativism and empiricism: it starts from the principle of structural dependency; all else is analogy.
Mineral Metabolism Markers Are Associated with Myocardial Infarction and Hemorrhagic Stroke but Not Ischemic Stroke in Hemodialysis Patients: A Longitudinal Study

Background/Aims The associations between phosphate, calcium, and intact parathyroid hormone (PTH) levels and composite cardiovascular end points have been studied. This study examined the associations of these markers with myocardial infarction (MI) and stroke separately. Methods This is a longitudinal study on 65,849 hemodialysis patients from the Japan Renal Data Registry. Patients with prior events at baseline were excluded. Predictors were phosphate, albumin-corrected calcium, intact PTH, and calcium times phosphate product levels. Outcome was the first episode of MI or stroke during a 1-year observation period. Data were analyzed using multiple logistic regression analyses, adjusted for potential confounders. Results There were 1,048, 651, and 2,089 events of incident MI, hemorrhagic, and ischemic stroke, respectively. Incident MI was associated with phosphate levels ≥6.5 mg/dL (odds ratio 1.49; confidence interval 1.23–1.80) compared with phosphate levels of 4.7–5.4 mg/dL and intact PTH levels>500 pg/mL (1.35; 1.03–1.79) compared with intact PTH levels of 151–300 pg/mL. Higher albumin-corrected calcium level was positively associated with MI (p = 0.04 by trend analysis). Hemorrhagic stroke was associated only with intact PTH levels>500 pg/mL (1.54; 1.10–2.17). Incident ischemic stroke had no association with phosphate, calcium, or intact PTH levels. The association of calcium times phosphate product with outcomes was essentially the same pattern as that of phosphate and outcomes. Conclusions MI was associated with phosphate, calcium, and intact PTH levels, whereas hemorrhagic stroke was associated only with intact PTH. Ischemic stroke was not associated with any of them. The potential distinct beneficial effect on MI and stroke by managing bone and mineral disease should be investigated in future studies.
The Hunger Games: Embodied agents evolving foraging strategies on the frugal-greedy spectrum

In Evolutionary Biology and Game Theory, there is a long history of models aimed at predicting strategies adopted by agents during resource foraging. In Artificial Life, the agentbased modeling approach allowed to simulate the evolution of foraging behaviors in populations of artificial agents embodied in a simulated environment. In this paper, different sets of behaviors are evolved from a simple setting where agents seek for food patches distributed on a two-dimensional map. While agents are not explicitly playing a game of chicken, their strategies are found on a spectrum ranging from a frugal strategy (aka Dove) to a greedy strategy (aka Hawk). This phenomenon is due to the fact that moving is both a way for the agents to play or go to get away from an unfavorable area of the environment. It is also observed that by moving away, the agents preserve the ecology, preventing the resource from disappearing locally. Those strategies are shown to be stable if the environment is colonized by one given population. However, post-mortem tournaments among different groups of agents (separately evolved), systematically result in a specific group of agents dominating. The optimal strategy in the simulated tournaments is found to be one with fine-tuned timing for leaving. Further analysis shows how the strategy exploits resources without completely depleting them, producing Volterra-like population tendencies.
Parental networks, ethnicity, and social and cultural capital: the societal dynamics of educational resilience in Turkey

Abstract Resilience research has increasingly gained ground in the field of education research, due to its potential for ameliorating inequalities. This article deals with the emergence of educational resilience, with particular attention to parental network structure, by employing a Bourdieusian social and cultural capital approach. While much of the literature discusses resilience normatively as a personal trait, this article frames it as an outcome of larger societal processes. Drawing on a comparative study of the experiences of resilient student–mother and dropout–mother pairs living in inner-city areas of Istanbul, the article illustrates that the emergence of resilience is strongly linked to resources such as parental networks and that parental networks significantly differ along the nexus of ethnicity.
A Formal Specification in B of an Operating System

Operating system (OS), as a significant system software, provides services and security protection to a variety of applications. Thus, the correctness of OS is a core issue of computer systems. To ensure the correctness of operating systems, it is a recognized way to use the rigorous formal methods. In this paper, we apply B method to design a formal model of OS called fmC/OS. The process is split into two phases. At first, software document specifications are formal- ized into an abstract model and then the abstract model is implemented into the concrete model. The concrete model is the base of translating executable code. Operating System based on B method can strengthen validity and security of the system.
The Effect of Clustering in the Apriori Data Mining Algorithm: A Case Study

— Many organizations collect and store data about their customers, suppliers and business partners. However, much of the useful marketing insights are hidden in that enormous amount of data. Data mining is the process of searching and analyzing data in order to find potentially useful information. Although data mining consists of a broad family of computational methods and algorithms, for this study, we have chosen the Apriori algorithm as the basis of the data analysis framework. The objective of the paper is to present the effect of clustering the data onto the association rules. Hence, we have compared the results of two different approaches: Finding association rules without consumer segmentation, and with consumer segmentation. The data analysis framework is applied to the data of mobile operating systems' users. By extracting most important information from consumer data, we claim that this framework directs providers offer the right product/advertisement to the right consumer. I. INTRODUCTION The rapid growth of the smart phone applications market has fundamentally changed the way in which people access and consume content. This has contributed to a shift in competitive dynamics that impact network operators, operating system (OS)/ application store developers and handset manufacturers. According to Gartner Inc, free applications will account for 89% of total downloads in 2012. Worldwide mobile application store downloads will surpass 45.6 billion in 2012, with paid-for downloads totaling $5 billion [1]. In 2016, total global mobile application revenue is expected to reach $46 billion according to ABI Research. In this context, consumer's tendency to smart phone and accordingly to mobile OS market becomes more and more important. A fundamental truth in the business is that competitors have always an eye to others' customers. Besides, many customers are on the lookout for better services. It is known that acquiring new customers is more expensive than retaining them, an efficient customer retention strategy is crucial to a company's success [2]. This study focuses on finding behavioral patterns of consumers of mobile OSs. We believe that such knowledge would not only direct firms in the developing process of
PACKING AND OPTIMIZING THE CENTER OF GRAVITY LOCATION USING A GENETIC ALGORITHM

This paper presents a computer based methodology to solve packing type problems, and applies it to the placement of goods in a rectangular volume such as a tractor trailer, in order to obtain a desired center of gravity. These goods are assumed to be in the form of rectangular boxes of sizes such that they individually fit in the enclosing volume. The methodology proposed uses Genetic Algorithms (GAs) to obtain a near optimal placement of parts. GAs use the principles of natural selection to obtain this optimal placement. These principles, reproduction, crossover, and mutation, are used to construct feasible solutions from a set of candidate arrangements. The best of these are selected and substituted in the space of possible arrangements until convergence to a solution occurs. The methodology finds a solution without any operator input, and is applied successively to one dimensional, two dimensional, and two and a half dimensional type packing problems.
Radio Halos of Galaxy Clusters from Hadronic Secondary Electron Injection in Realistic Magnetic Field Configurations

We investigate the possibility that radio halos of clusters of galaxies are caused by synchrotron emission of cosmic ray electrons (CRe), which were produced by cosmic ray protons (CRp) interacting hadronically with the intra-cluster medium (ICM) protons. We perform cosmological magneto-hydrodynamics (MHD) simulations to obtain a sample of ten magnetized galaxy clusters. They provide realistic models of the gas and magnetic field distribution, needed to predict the CRe production rates, their cooling, and their synchrotron emissivity. We assume a CRp population within the ICM with an energy density which has a constant ratio to thermal energy density. This ratio is adjusted in such a way that one of the simulated clusters reproduces the radio luminosity of the radio halo of the Coma cluster of galaxies. Our model exhibits the observed low degree of radio polarization and has a similar radial emission profile as the Coma cluster. We provide estimates for the expected gamma ray and neutrino flux. The necessary CRp/thermal energy ratio is 4 . 14% ${(E_{p,min}/GeV)}^{-0.375}$ (for the range of magnetic field strengths suggested by Faraday measurements), where $E_{p,min}$ is the lower kinetic energy cutoff of the CRp with spectral index $\alpha_p \approx 2.375$. Assuming this ratio to be the same in the whole set of simulated clusters a $T_x-L_\nu$ relation is predicted which follows the observed relation well.
Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images

This paper investigates the use of machine learning classification techniques applied to the task of recognising the make and model of vehicles. Although a number of vehicle classification systems already exist, most of them seek only to distinguish between vehicle categories, e.g. identifying whether a vehicle is a bus, truck or car. The system presented here demonstrates that a set of features extracted from the frontal view of a vehicle may be used to determine the vehicle type (make and model) with high accuracy. The performance of some standard multi-class classification algorithms is compared for this problem. A one-class k-Nearest Neighbour classification algorithm is also implemented and tested.
The High Prevalence of Anemia in Cambodian Children and Women Cannot Be Satisfactorily Explained by Nutritional Deficiencies or Hemoglobin Disorders

Background: Anemia is highly prevalent in Cambodian women and children, but data on causes of anemia are scarce. We performed a national micronutrient survey in children and women that was linked to the Cambodian Demographic Health Survey 2014 (CDHS-2014) to assess the prevalence of micronutrient deficiency, hemoglobin disorders and intestinal parasite infection. Methods: One-sixth of households from the CDHS-2014 were selected for a follow-up visit for the micronutrient survey. Households were visited from two weeks to two months after the CDHS-2014 visit. Data on micronutrient status were available for 1512 subjects (792 children and 720 women). Results: Anemia was found in 43% of the women and 53% of the children. Hemoglobin disorders affected >50% of the population, with Hemoglobin-E the most prevalent disorder. Deficiencies of iron (ferritin < 15 g/L), vitamin A (retinol-binding-protein (RBP) < 0.70 mol/L) or vitamin B12 (<150 pmol/L) were not prevalent in the women (<5% for all), whereas 17.8% of the women had low concentrations of folic acid (<10 nmol/L). In the children, the prevalence of iron, vitamin A, vitamin B12 or folic acid deficiency was <10%. Zinc deficiency, hookworm infection and hemoglobinopathy were significantly associated with anemia in children, whereas in the women none of the factors was significantly associated with anemia. Iron deficiency anemia (IDA) was more prevalent in children <2 years, but in older children and women, the prevalence of IDA was <5%. The most prevalent, preventable causes of anemia were hookworm infection and zinc and folic acid deficiency. Over 40% of the anemia was not caused by nutritional factors. Conclusion: The very high prevalence of anemia in Cambodian women and children cannot be explained solely by micronutrient deficiencies and hemoglobin disorders. Micronutrient interventions to improve anemia prevalence are likely to have limited impact in the Cambodian setting. The focus of current interventions to reduce the high prevalence of anemia in children and women should be broadened to include zinc and folic acid as well as effective anti-hookworm measures.