On Colorful Bin Packing Games

We consider colorful bin packing games in which selfish players control a set of items which are to be packed into a minimum number of unit capacity bins. Each item has one of $m\geq 2$ colors and cannot be packed next to an item of the same color. All bins have the same unitary cost which is shared among the items it contains, so that players are interested in selecting a bin of minimum shared cost. We adopt two standard cost sharing functions: the egalitarian cost function which equally shares the cost of a bin among the items it contains, and the proportional cost function which shares the cost of a bin among the items it contains proportionally to their sizes. Although, under both cost functions, colorful bin packing games do not converge in general to a (pure) Nash equilibrium, we show that Nash equilibria are guaranteed to exist and we design an algorithm for computing a Nash equilibrium whose running time is polynomial under the egalitarian cost function and pseudo-polynomial for a constant number of colors under the proportional one. We also provide a complete characterization of the efficiency of Nash equilibria under both cost functions for general games, by showing that the prices of anarchy and stability are unbounded when $m\geq 3$ while they are equal to 3 for black and white games, where $m=2$. We finally focus on games with uniform sizes (i.e., all items have the same size) for which the two cost functions coincide. We show again a tight characterization of the efficiency of Nash equilibria and design an algorithm which returns Nash equilibria with best achievable performance

Epidemic processes in complex networks

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

TESPAR Coded Speech Quality Evaluation (TCSQE) : A New Algorithm for Objective Measurement of Speech Quality in Cellular Networks

Speech transmission quality measurement in cellular networks is a major indicator of performance for end-to-end quality of service standards. Many approaches have been proposed in the previous studies, but the results correlation with subjective experiments still need further optimization, especially for quality determination using languages with unique phonetic structures i.e. clicking sounds. Moreover, the evaluation test data is always a key element in order to obtain representative and consistent results. In this paper, we introduce TESPAR coding technique for the design of a new algorithm for speech (voice) quality measurement in cellular/wireless telecommunication networks. Our experiments show that the results from this algorithm correlates well with subjective experiments using a variety of speech samples. The proposed algorithm is also computationally efficient than the existing methods and is suitable for quality measurement of longer speech signals than the current 8 seconds speech test data mostly in use today

Inheritance patterns in citation networks reveal scientific memes

Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and we validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.Comment: 8 two-column pages, 5 figures; accepted for publication in Physical Review

Case Report Protein-Loosing Entropathy Induced by Unique Combination of CMV and HP in an Immunocompetent Patient

Protein-losing gastroenteropathies are characterized by an excessive loss of serum proteins into the gastrointestinal tract, resulting in hypoproteinemia (detected as hypoalbuminemia), edema, and, in some cases, pleural and pericardial effusions. Protein-losing gastroenteropathies can be caused by a diverse group of disorders and should be suspected in a patient with hypoproteinemia in whom other causes, such as malnutrition, proteinuria, and impaired liver protein synthesis, have been excluded. In this paper, we present a case of protein-losing enteropathy in a 22-year-old immunocompetent male with a coinfection of CMV and Hp

GAN-based multiple adjacent brain MRI slice reconstruction for unsupervised alzheimer’s disease diagnosis

Unsupervised learning can discover various unseen diseases, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstruct a single medical image to detect outliers either in the learned feature space or from high reconstruction loss. However, without considering continuity between multiple adjacent slices, they cannot directly discriminate diseases composed of the accumulation of subtle anatomical anomalies, such as Alzheimer's Disease (AD). Moreover, no study has shown how unsupervised anomaly detection is associated with disease stages. Therefore, we propose a two-step method using Generative Adversarial Network-based multiple adjacent brain MRI slice reconstruction to detect AD at various stages: (Reconstruction) Wasserstein loss with Gradient Penalty + L1 loss---trained on 3 healthy slices to reconstruct the next 3 ones---reconstructs unseen healthy/AD cases; (Diagnosis) Average/Maximum loss (e.g., L2 loss) per scan discriminates them, comparing the reconstructed/ground truth images. The results show that we can reliably detect AD at a very early stage with Area Under the Curve (AUC) 0.780 while also detecting AD at a late stage much more accurately with AUC 0.917; since our method is fully unsupervised, it should also discover and alert any anomalies including rare disease.Comment: 10 pages, 4 figures, Accepted to Lecture Notes in Bioinformatics (LNBI) as a volume in the Springer serie

Caffeine vs. carbamazepine as indicators of wastewater pollution in a karst aquifer

This paper presents the analysis of caffeine and carbamazepine transport in the subsurface as a result of wastewater release in the Sorek creek over the outcrops of the carbonate, Yarkon-Taninim, aquifer in Israel. Both caffeine and carbamazepine were used as indicators of sewage contamination in the subsurface. While carbamazepine is considered conservative, caffeine is subject to sorption and degradation. The objective of the study was to quantify differences in their transport under similar conditions in the karst aquifer. Water flow and pollutant transport in a “vadose zone–aquifer” system were simulated by a quasi-3-D dual permeability numerical model. The results of this study show that each of these two pollutants can be considered effective tracers for characterization and assessment of aquifer contamination. Carbamazepine was found to be more suitable for assessing the contamination boundaries, while caffeine can be used as a contaminant tracer only briefly after contamination occurs. In instances where there are low concentrations of carbamazepine which appear as background contamination in an aquifer, caffeine might serve as a better marker for detecting new contamination events, given its temporal nature. The estimated caffeine degradation rate and the distribution coefficient of a linear sorption isotherm were 0.091&thinsp;d−1 and 0.1&thinsp;L&thinsp;kg−1, respectively, which imply a high attenuation capacity. The results of the simulation indicate that by the end of the year most of the carbamazepine mass (approximately 95&thinsp;%) remained in the matrix of the vadose zone, while all of the caffeine was completely degraded a few months after the sewage was discharged.</p

Gene and protein nomenclature in public databases

BACKGROUND: Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap. RESULTS: We compiled five gene and protein name dictionaries for each of the five model organisms (yeast, fly, mouse, rat, and human) from different organism-specific and general public databases. We analyzed the degree of ambiguity of gene and protein names within and between dictionaries, to a lexicon of common English words and domain-related non-gene terms, and we compared different data sources in terms of size of extracted dictionaries and overlap of synonyms between those. The study shows that the number of genes/proteins and synonyms covered in individual databases varies significantly for a given organism, and that the degree of ambiguity of synonyms varies significantly between different organisms. Furthermore, it shows that, despite considerable efforts of co-curation, the overlap of synonyms in different data sources is rather moderate and that the degree of ambiguity of gene names with common English words and domain-related non-gene terms varies depending on the considered organism. CONCLUSION: In conclusion, these results indicate that the combination of data contained in different databases allows the generation of gene and protein name dictionaries that contain significantly more used names than dictionaries obtained from individual data sources. Furthermore, curation of combined dictionaries considerably increases size and decreases ambiguity. The entries of the curated synonym dictionary are available for manual querying, editing, and PubMed- or Google-search via the ProThesaurus-wiki. For automated querying via custom software, we offer a web service and an exemplary client application

Original Contribution Do Psychosocial Stress and Social Disadvantage Modify the Association Between Air Pollution and Blood Pressure? The Multi-Ethnic Study of Atherosclerosis

Researchers have theorized that social and psychosocial factors increase vulnerability to the deleterious health effects of environmental hazards. We used baseline examination data (2000)(2001)(2002) from the Multi-Ethnic Study of Atherosclerosis. Participants were 45-84 years of age and free of clinical cardiovascular disease at enrollment (n = 6814). The modifying role of social and psychosocial factors on the association between exposure to air pollution comprising particulate matter less than 2.5 µm in aerodynamic diameter (PM 2.5 ) and blood pressure measures were examined using linear regression models. There was no evidence of synergistic effects of higher PM 2.5 and adverse social/psychosocial factors on blood pressure. In contrast, there was weak evidence of stronger associations of PM 2.5 with blood pressure in higher socioeconomic status groups. For example, those in the 10th percentile of the income distribution (i.e., low income) showed no association between PM 2.5 and diastolic blood pressure (b = −0.41 mmHg; 95% confidence interval: −1.40, 0.61), whereas those in the 90th percentile of the income distribution (i.e., high income) showed a 1.52-mmHg increase in diastolic blood pressure for each 10-µg/m 3 increase in PM 2.5 (95% confidence interval: 0.22, 2.83). Our results are not consistent with the hypothesis that there are stronger associations between PM 2.5 exposures and blood pressure in persons of lower socioeconomic status or those with greater psychosocial adversity. air pollution; blood pressure; population groups; social environment; social medicine; social psychology Abbreviations: CVD, cardiovascular disease; DBP, diastolic blood pressure; ETS, exposure to second-hand smoke; MAP, mean arterial pressure; MESA, Multi-Ethnic Study of Atherosclerosis; PM 2.5 , particulate matter less than 2.5 µm in aerodynamic diameter; PP, pulse pressure; SBP, systolic blood pressure; SES, socioeconomic status