Analyzing complexity in foreign language monologic oral production in a CLIL context

The study tested three analytic tools applied in SLA research (T-unit, AS-unit and Idea-unit) against FL learner monologic oral data. The objective was to analyse their effectiveness for the assessment of complexity of learners' academic production in English. The data were learners' individual productions gathered during the implementation of a CLIL teaching sequence on Natural Sciences in a Catalan state secondary school. The analysis showed that only AS-unit was easily applicable and highly effective in segmenting the data and taking complexity measures

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Strong isomorphism reductions in complexity theory

We give the first systematic study of strong isomorphism reductions, a notion of reduction more appropriate than polynomial time reduction when, for example, comparing the computational complexity of the isomorphim problem for different classes of structures. We show that the partial ordering of its degrees is quite rich. We analyze its relationship to a further type of reduction between classes of structures based on purely comparing for every n the number of nonisomorphic structures of cardinality at most n in both classes. Furthermore, in a more general setting we address the question of the existence of a maximal element in the partial ordering of the degrees.

Systematic survey of clonal complexity in tuberculosis at a populational level and detailed characterization of the isolates involved.

Clonally complex infections by Mycobacterium tuberculosis are progressively more accepted. Studies of their dimension in epidemiological scenarios where the infective pressure is not high are scarce. Our study systematically searched for clonally complex infections (mixed infections by more than one strain and simultaneous presence of clonal variants) by applying mycobacterial interspersed repetitive-unit (MIRU)-variable-number tandem-repeat (VNTR) analysis to M. tuberculosis isolates from two population-based samples of respiratory (703 cases) and respiratory-extrapulmonary (R+E) tuberculosis (TB) cases (71 cases) in a context of moderate TB incidence. Clonally complex infections were found in 11 (1.6%) of the respiratory TB cases and in 10 (14.1%) of those with R+E TB. Among the 21 cases with clonally complex TB, 9 were infected by 2 independent strains and the remaining 12 showed the simultaneous presence of 2 to 3 clonal variants. For the 10 R+E TB cases with clonally complex infections, compartmentalization (different compositions of strains/clonal variants in independent infected sites) was found in 9 of them. All the strains/clonal variants were also genotyped by IS6110-based restriction fragment length polymorphism analysis, which split two MIRU-defined clonal variants, although in general, it showed a lower discriminatory power to identify the clonal heterogeneity revealed by MIRU-VNTR analysis. The comparative analysis of IS6110 insertion sites between coinfecting clonal variants showed differences in the genes coding for a cutinase, a PPE family protein, and two conserved hypothetical proteins. Diagnostic delay, existence of previous TB, risk for overexposure, and clustered/orphan status of the involved strains were analyzed to propose possible explanations for the cases with clonally complex infections. Our study characterizes in detail all the clonally complex infections by M. tuberculosis found in a systematic survey and contributes to the characterization that these phenomena can be found to an extent higher than expected, even in an unselected population-based sample lacking high infective pressure.

Shape complexity based on mutual information

Shape complexity has recently received attention from different fields, such as computer vision and psychology. In this paper, integral geometry and information theory tools are applied to quantify the shape complexity from two different perspectives: from the inside of the object, we evaluate its degree of structure or correlation between its surfaces (inner complexity), and from the outside, we compute its degree of interaction with the circumscribing sphere (outer complexity). Our shape complexity measures are based on the following two facts: uniformly distributed global lines crossing an object define a continuous information channel and the continuous mutual information of this channel is independent of the object discretisation and invariant to translations, rotations, and changes of scale. The measures introduced in this paper can be potentially used as shape descriptors for object recognition, image retrieval, object localisation, tumour analysis, and protein docking, among others

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.

Detection of the B"-GWGR variant in the southernmost region of Brazil: unveiling the complexity of the human immunodeficiency virus-1 subtype B epidemic

Typical human immunodeficiency virus-1 subtype B (HIV-1B) sequences present a GPGR signature at the tip of the variable region 3 (V3) loop; however, unusual motifs harbouring a GWGR signature have also been isolated. Although epidemiological studies have detected this variant in approximately 17-50% of the total infections in Brazil, the prevalence of B"-GWGR in the southernmost region of Brazil is not yet clear. This study aimed to investigate the C2-V3 molecular diversity of the HIV-1B epidemic in southernmost Brazil. HIV-1 seropositive patients were ana-lysed at two distinct time points in the state of Rio Grande do Sul (RS98 and RS08) and at one time point in the state of Santa Catarina (SC08). Phylogenetic analysis classified 46 individuals in the RS98 group as HIV-1B and their molecular signatures were as follows: 26% B"-GWGR, 54% B-GPGR and 20% other motifs. In the RS08 group, HIV-1B was present in 32 samples: 22% B"-GWGR, 59% B-GPGR and 19% other motifs. In the SC08 group, 32 HIV-1B samples were found: 28% B"-GWGR, 59% B-GPGR and 13% other motifs. No association could be established between the HIV-1B V3 signatures and exposure categories in the HIV-1B epidemic in RS. However, B-GPGR seemed to be related to heterosexual individuals in the SC08 group. Our results suggest that the established B"-GWGR epidemics in both cities have similar patterns, which is likely due to their geographical proximity and cultural relationship.

Epidemiological and clinical complexity of amoxicillin-clavulanate-resistant Escherichia coli.

Two hundred twelve patients with colonization/infection due to amoxicillin-clavulanate (AMC)-resistant Escherichia coli were studied. OXA-1- and inhibitor-resistant TEM (IRT)-producing strains were associated with urinary tract infections, while OXA-1 producers and chromosomal AmpC hyperproducers were associated with bacteremic infections. AMC resistance in E. coli is a complex phenomenon with heterogeneous clinical implications.