Miracle-dz/UniFAR-FTUs huggingface dataset:
Comment

(2003a), Envisioning Information, Cheshire, CT: Graphics Press. (2003b), Visual Explanations: Images and Quantities, Evidence and Narrative, Cheshire, CT: Graphics Press. Tukey, J. W. (1962), “The Future of Data Analysis,” Annals of Mathematical Statistics, 33, 1–67. (1977), Exploratory Data Analysis, Reading, MA: Addison-Wesley. (1982), “Another Look at the Future,” in Computer Science and Statistics: Proceedings of the 14th Symposium on the Interface, pp. 2–8. (1986), “The Interface With Computing: In the Small or in the Large? ” in Computing Science and Statistics: Proceedings of the 18th Symposium on the Interface, pp. 3–7. Tukey, J. W. , and Tukey, P. A. (1985), “Computer Graphics and Exploratory Data Analysis: An Introduction,” in Proceedings of the Sixth Annual Conference and Exposition: Computer Graphics85, Fairfax, VA: National Computer Graphics Association. Tversky, B. , Morrison, J. B. , and Bétrancourt, M. (2002), “Animation: Can It Facilitate? ” International Journal of Human–Computer Studies, 57, 247– 262. Wadlow, T. A. (1981), “The Xerox Alto Computer,” Byte, 6, 58–68. Wand, Y. , and Wang, R. Y. (1996), “Anchoring Data Quality Dimensions in Ontological Foundations,” Communications of the ACM, 39, 86–95. Wang, A. (1986), Lessons: An Autobiography, Reading, MA: Addison-Wesley. Wickham, H. , and Hofmann, H. (2007), “Scagnostics in R,” presented at 2007 Joint Statistical Meetings, Salt Lake City, UT, July 29. Wilkinson, L. (2005), The Grammar of Graphics (2nd ed.), New York: Springer-Verlag. (2008), “FASTAT: Statistics Without Manuals, Menus, Mice,” in Statistical Graphics: Data and Information Visualization in Today’s Multimedia Society (DataViz VI), Jacobs University Bremen, Germany. Wilkinson, L. , Anand, A. , and Grossman, R. (2006), “High-Dimensional Visual Analytics: Interactive Exploration Guided by Pairwise Views of Point Distributions,” IEEE Transactions on Visualization and Computer Graphics, 12, 1363–1372. Wills, G. (2007), “Scagnostic-Driven Autovisualization,” presented at 2007 Joint Statistical Meetings, Salt Lake City, UT, July 29. Wood, J., Dykes, J., Slingsby, A. , and Clarke, K. (2007), “Interactive Visual Exploration of a Large Spatio-Temporal Dataset: Reflections on a Geovisualization Mashup,” IEEE Transactions on Visualization and Computer Graphics, 13, 1176–1183.
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because it does perfectly capture the middle that is excluded by probability theory. Supposing that nature can crisply classify today as “warm” (W = 1) or “not warm” (W = 0), then a subjective you or I can assign uncertainties to the set {0,1} of possible values of W by associating “basic probabilities” a, b, and c with a + b + c = 1 to the subsets {1}, {0}, {0,1}, where the empty set is excluded and the full set {0,1} is included as a special type of “subset. ” Standard DS terminology then calls a the “belief” that W = 1 and a + c the “plausibility” that W = 1. “Belief” includes only the “basic probability” a that must be associated with W = 1, “plausibility” adds in “basic probability” c that can be associated with W = 1 or 0. “Belief” is the probability that W = 1 that we are sure of, and whereas thus should be willing to bet with. To allay concerns that DS theory deals with belief in the sense of religious faith, I subsequently refer to “belief” simply as “probability,” and use Pr(x) and Pl(x) to denote probability and plausibility. To reproduce a Zadeh-type of membership function via DS theory, we simply make b = 0 in the foregoing notation so that Pr(1) = a and can be interpreted as membership m(1) = a. This type of DS model can be called “simple support. ” It is unidirectional in the sense that Pr(0) = 0, so that no support is offered to W = 0. Jacob Bernoulli in Ars Conjectandi, called simple support a “pure argument,” because it cuts only one way. Of course, in the DS system there is no need to require b = 0, so we can have a fuzzy logic with both probable and plausible membership values less than unity. If the machinery of DS theory is accepted as a basis for fuzzy logic, at least sometimes, then a well-tested set of tools becomes available, including the rule for combining independent belief function formulations of evidence and associated models with graphical structure including hidden Markov models. For example, Dempster and Chiu (2003) are developing tools for supervised machine learning based on DS theory. There is no barrier in the way of the development of DS methods for most complex data types that statistical practice increasingly confronts, only issues of model and algorithm construction.
LISTERIA MONOCYTOGENES DANS LES PRODUITS DE LA PÊCHE

Listeria monocytogenes is a pathogenic bacterium, psychrotrophic and ubiquitous. It causes listeriosis, a mainly foodborne infection which can be serious, and sometimes even fatal in populations at risk (pregnant women, the elderly, immunodeficient patients). Various seafood products have been incriminated in invasive and non-invasive listeriosis. Listeria growth rates can be significant at the refrigeration temperatures (0 to 8 °C) commonly used in the seafood industry. L. monocytogenes is found in both raw materials and in the processing environment (resident strains). The strains isolated from seafood products were generally virulent. The implementation of good practices, from the producer to the consumer, helps limit the development of L. monocytogenes in seafood products.
L’activation/dégradation protéasomique des GTPases Rho par CNF1 confère des capacités invasives aux E. coli uropathogènes

nente des GTPases Rho (Figure 1). CNF1 partage, avec une vingtaine de facteurs de virulence bactériens connus, la propriété biochimique de modification des GTPases Rho (pour revue, voir [3]). Les protéines Rho semblent être en amont de cascades moléculaires commandant les remaniements du cytosquelette d’actine nécessaires à la phagocytose, à la migration et à la différenciation cellulaires [8]. L’activation de Rac et de CDC42 produit la formation de projections membranaires notamment impliquées dans la phagocytose de type Fcγ alors que le contrôle de l’état de contraction de l’actine par Rho participe à la phagocytose de type complément [9]. Rac contrôle également la formation d’espèces actives de l’oxygène en réponse aux pathogènes. Il partage aussi avec Rho et CDC42 le contrôle de la régulation de la synthèse de produits inflammatoires et de molécules proou antiapoptotiques. Il est vraisemblable que la forte occurrence de facteurs de virulence dirigés contre ces protéines soit la conséNO UV EL LE S M AG AZ IN E
Evaluation of some coccinellid species for the biological control of aphids in protected cropping

SUMMARY Four species of Coccinellidae, Adalia bipunctata (L.), Coccinella septem-punctata L. , Coelomegilla maculata de G. and Cycloneda sanguinea L. , were compared as predators of aphids on cucumbers and chrysanthemums. In laboratory feeding tests C. maculata and C. sanguinea proved the most voracious but the former could not remain on cucumber foliage long enough to be effective. The fecundity of C. sanguinea was the highest of those studied and a satisfactory laboratory rearing technique has been developed for this species.
Comment

Duchi, Wainwright, and Jordan took on a more statistical perspective introducing an underlying distribution family from which the data are drawn. In our simple example, we might assume that the bits xi are drawn from a Bernoulli distribution with parameter p. The goal is then to estimate the parameter p rather than to return an approximation of the samplemean. This viewpoint fits nicely with the minimax framework of statistical estimation. Once posed this way, minimax lower bounds are developed through classical information-theoretical tools such as the inequalities of Le Cam, Fano, and Assouad. To summarize the many results the authors obtain, the sample requirements under -differential privacy in the local model generally increase by a factor of 1/ compared with the standard requirements when no privacy constraint is imposed. At the heart of these lower bound results are packing arguments that expose collections of instances far in one metric, but close in another. In the parameter estimation case, such packings provide sets of parameters so that any two distinct parameters in the set are far in a desired error metric (e.g., Euclidean distance), but correspond to distributions close in a probability metric such total variation distance. Packing arguments had been the work horse of lower bounds in differential privacy before in both the centralized and local model. These earlier lower bounds, for example, Beimel, Nissim, and Omri (2008), and Hardt and Talwar (2010), focused on sample quantities. In this case, the packing contains databases of size n that are close in Hamming distance (i.e., have significant overlap), but map to sample quantities that are far in the error metric. The work of Duchi,Wainwright, and Jordan developed novel packing arguments and perturbation mechanisms for differential privacy in the minimax framework of statistical estimation leading to a range of minimax optimal estimation rates. As a beneficial side effect, the work introduced the theoretical computer science community interested in differential privacy to several important ideas and concepts in statistical estimation, thus fostering a healthy andmuch needed exchange between the fields. The sequence of papers by the authors also receivedmuch attention in the machine learning community, where it sparked increased interest in differential privacy.
Comment

that a researcher could take off-the-shelf and adapt to a particular setting. What should be taken away from the analysis here, and developed further, is an understanding of how to address issues of specification, endogeneity, omitted variables, measurement errors, etc., but not the particular functional forms for doing this. There are many channels for peer effects even restricting ourselves to an education setting: students study together, they may exert pressures on each other not to study, they might engage in illicit activities together, they may serve as role models for each other, they may feel pressures to conform, they may be searching for an identity and sense of belonging, they may experience parental influences, they may experience complementarities in their payoffs from the educational decisions, they may be exposed to stimuli that they react to communally, and so forth. Clearly, this long and still incomplete list of potential peer effects is unlikely to be all captured in a simple, for example linear, manner based on some measurement of a grade or other outcome. While this requires adding complexity to the modeling, being very explicit about the specific type of effect that one is seeking to identify is much more likely to yield a useful model. This is illustrated by Banerjee et al. (2012) who dissected peer effects in the context of word-of-mouth spread of a new product (microfinance in rural Indian villages). By explicitly modeling information passing in the network and fitting that model to data, they found that what appears to be a strongly positive peer/endorsement effect becomes insignificant (and even slightly negative) once one models information passing. An interpretation of their findings is that a given individual is more likely to participate when more friends do, is not due to some complementarity, peer influence, or endorsement effect, but rather because having more friends take up the product simply makes one more likely to be aware of the product. While the particulars of the finding are relative to the specifics of the setting, the broader message is that more explicit modeling of the details of peer interaction can lead to very different conclusions from what one might infer based on standard linear-in-means style regressions. More generally, such an approach will require models that account for the wide multitude of different forms of learning, peer influences, and peer interactions. These challenges become even more substantial when building models of peer effects that also incorporate network formation, as there can be complex feedbacks between behavior and friendship choices. While strategic network formation models have been studied in some detail in the theory literature (e.g., Jackson and Wolinsky 1996; Bala and Goyal 2000; Jackson 2008), models designed for empirical implementation of
Interactions between leaf water potential, stomatal conductance and abscisic acid content of orange trees submitted to drought stress

Laranjeiras 'Pera' de dois anos e meio de idade enxertadas em limoeiros 'Cravo' foram cultivadas em vasos de 100 L com solo e submetidas ao estresse hidrico, pela suspensao da irrigacao. Valores de assimilacao de CO2 (A), transpiracao (E) e condutância estomatica (gs) comecaram a declinar a partir do setimo dia de estresse, embora o potencial da agua na folha as 6 a.m. (Ypd) e as 2 p.m. (Y2) comecaram a declinar a partir do quinto dia de deficiencia hidrica. A concentracao interna de CO2 (Ci) das plantas estressadas aumentou a partir do mesmo dia, atingindo uma concentracao maxima no dia de estresse mais severo. Assim, a eficiencia de carboxilacao dessas plantas, verificada pela relacao A/Ci foi menor nesse dia, nao ocorrendo recuperacao dessa razao mesmo dez dias apos a reidratacao. Ate o quinto dia apos a reirrigacao, somente o Ypd e o Y2 se recuperaram, sendo semelhantes aos das plantas controle. Quando o potencial da agua na folha diminuiu, ocorreu uma tendencia de aumento da concentracao de acido abscisico (ABA) nas folhas; da mesma forma, foi possivel verificar que a condutância estomatica diminuiu em funcao do decrescimo em Y2. O acumulo de ABA e o fechamento estomatico ocorreram quando Y2 foi menor que -1.0 MPa. A deficiencia hidrica em laranjeiras 'Pera' aumentou o conteudo de ABA, com consequente fechamento estomatico e decrescimo em Y2.
Arachidonic Acid and Bovine Corpus Luteum Function 1

Summary Injections of arachidonic acid directly into the corpora lutea of normal cattle at the 12th or 13th day of the estrous cycle resulted in (a) a decline in jugular vein plasma progesterone levels from an average of 6 ng/ml to 2.5 ng/ml (P < 0.05), (b) an immediate rise in PGF levels in ovarian venous plasma, and (c) a sharp rise in jugular vein plasma estrogen levels. Jugular plasma estrogen peaks were associated with each ovarian vein PGF peak in each animal; jugular plasma LH levels did not change. These results show that the bovine ovary can convert arachidonic acid to PGF and that arachidonic acid administered directly into the corpus luteum results in partial regression of the corpus luteum. PGF appears to stimulate estrogen production by the ovary in the absence of measurable changes of plasma LH. The technical assistance of R. Saatman and Denise Lensing is gratefully acknowledged.
Genome-wide Approaches to Investigate and Improve Maize Response to Drought

Genome-wide, approaches offer new, unprecedented opportunities to identify, clone, and manipulate the plethora of genes affecting drought tolerance in model species and crops. Compared to conventional breeding approaches, the dissection of the genetic basis of quantitative traits into their single components (i.e., quantitative trait loci [QTLs]) provides a more direct access to valuable genetic diversity of the morpho-physiological processes regulating the adaptive response to drought. This, in turn enables as to utilize marker-assisted the impressive progress in molecular techniques and the number of OTLs shown to influence yield in drought-stressed crops, the overall impact of MAS on the release of drought-tolerant cultivers has so far been marginal. It i able that QTL cloning will be facilitated by sequence information and the profiling of the transcriptome proteame, and metabolome, all of which will improve the identification of plausible candidate genes. The cloning of major QTLs will offer additional opportunities for a more effective exploitation of the allelic rickness present in germplasm collections. Allele mining in germplasm and mutant collections through forward- and reverse-genetics approaches coupled with marker-assisted backcrossing and/or genetic engineering, will further expand the possibilities to introgress novel genetic variation in elite capacity to undersdant the genetic and molecular basic of genotype × environment interaction at varying water regimes, will contribute to singling out the most promising "molecular" ideotypes. This notwithstanding, a sizeable impact of MAS and other genomics approaches on the release of cultivars more resilient to drought will only be possible through (i) a deeper integation with conventional breeding methodologies, (ii) the capacity to accurately phenotype on a large scale, and (iii) a sound multidisciplinary knowledge of the biochemical and physiological processes determining crops' yield and its stability under a broad range of water regimes.
Imposing and Testing Curvature Conditions on a Box–Cox Cost Function

We present a new method for imposing and testing concavity of cost functions using asymptotic least squares, which can be easily implemented even for nonlinear cost functions. We provide an illustration for a (generalized) Box–Cox cost function with six inputs: capital, labor disaggregated in three skill levels, energy, and intermediate materials. We present a parametric concavity test and compare price elasticities when curvature conditions are imposed versus when they are not. Although concavity is statistically rejected, estimates are not very sensitive to its imposition. We find stronger substitution between the different type of labor than between any other two inputs.
Rejoinder

NOTE: The case-based scheme results in eigenvalue estimates that are even more extreme than the true values, an exacerbated sorting bias. The unit-based resampling ameliorates the bias problem to a limited extent; the first eigenvalue is still overestimated and the third is still underestimated, but the bias is not as large. an article that presents both possible solutions and stimulus for research in new directions.
Comment

1. Bickel and Ritov (1 994) found it useful to consider essentially the MPLE approach but applied to the distribution of T n ( X 1 ) , . , Tn(Xn) , where T, converges to the identity in an appropriate sense. Thus the MPLE for the transformed model was efficient in situations where the MPLE for the original model was not consistent. 2. Bickel et al. (1991) considered a situation in which the MPLE was not appropriate but q could be estimated effi5. PHILOSOPHICAL NOTE
Diagnostic molecular markers discriminating Africanized honey bees from Greek and Cypriot honey bees (Apis mellifera, Hymenoptera: Apidae)

Summary Diagnostic patterns using PCR—RFLPs analysis of two mtDNA gene segments (16s rDNA and CO I) were shown to discriminate Africanized honey bees from Greek and Cypriot honey bees; high values of net nucleotide sequence divergence were observed among Africanized honey bees and the other populations studied. The tree obtained by UPGMA method ensured that the Africanized honey bee is discriminated from the honey bee populations from Greece and Cyprus. These results could be useful for the early detection of Africanized honey bees.
A new generation of climate‐change experiments: events, not trends

Intensification of weather extremes is currently emerging as one of the most important facets of climate change. Research on extreme events (“event-focused” in contrast to “trend-focused”) has increased in recent years and, in 2004, accounted for one-fifth of the experimental climate-change studies published. Numerous examples, ranging from microbiology and soil science to biogeography, demonstrate how extreme weather events can accelerate shifts in species composition and distribution, thereby facilitating changes in ecosystem functioning. However, assessing the importance of extreme events for ecological processes poses a major challenge because of the very nature of such events: their effects are out of proportion to their short duration. We propose that extreme events can be characterized by statistical extremity, timing, and abruptness relative to the life cycles of the organisms affected. To test system response to changing magnitude and frequency of weather events, controlled experiments are useful tools. These experiments provide essential insights for science and for societies that must develop coping strategies for such events. Here, we discuss future research needs for climate-change experiments in ecology. For illustration, we describe an experimental plan showing how to meet the challenge posed by changes in the frequency or magnitude of extreme events.
Comment

The article by Goldsmith-Pinkham and Imbens (2013) is an interesting contribution to the literature on social interactions. An important contribution of their article is to provide some answers to the question: what features of models of social interactions are empirically relevant? This question concerns the relationship between the true data-generating process and the model used by the econometrician. In our comment on their article, we ask an alternative question: how should policy makers use the estimates from the linear-in-means model? This question concerns the relationship between the model used by the econometrician and policy interventions. The scope of our comment extends beyond the article by Goldsmith-Pinkham and Imbens (2013) to address this issue in the general linear-in-means model literature. We first derive standard marginal effects of a change in a covariate. These are complicated functions of the model parameters. This suggests that it may be useful for applications of the linear-in-means model to report these policy relevant parameters. Another interpretation views the linear-in-means model as a best response function from some game. This gives an autonomous interpretation to the parameters and uncovers the mechanisms underlying the interaction. This approach, though natural in economics, is based on a very particular model of interaction.
Clinical virology of cytomegalovirus infection following hematopoietic transplantation

Cytomegalovirus (CMV) causes significant morbidity and mortality in allogeneic stem cell transplant recipients. The incidence of early CMV disease has been dramatically reduced by use of preemptive therapeutic strategies. Nevertheless, a trend toward a later appearance of CMV disease is being increasingly recognized. Currently, quantitative real-time PCR assays are the first-line choice for monitoring active CMV infection. However, no threshold DNAemia levels for triggering the initiation of preemptive therapy have been clinically validated in large studies. Although more time limited than universal prophylaxis, preemptive therapy strategies may also result in over treatment. Combined virological and immunological monitoring may lead to a more targeted use of antiviral therapy. The emergence of CMV strains resistant to antivirals is unfrequent, and must be suspected when rising viral DNAemia levels are observed after several weeks of treatment in the context of a severe immunosuppressive state. Genotypic .