Parent-child interaction in Nigerian families: conversation analysis, context and culture

This paper uses a conversation analysis (CA) approach to explore parent child interaction (PCI) within Nigerian families. We illustrate how speech and language therapists (SLTs), by using CA, can tailor recommendations according to the interactional style of each individual family that are consonant with the family’s cultural beliefs. Three parent-child dyads were videoed playing and talking together in their home environments. The analysis uncovered a preference for instructional talk similar to that used in the classroom. Closer examination revealed that this was not inappropriate when considering the context of the activities and their perceived discourse role. Furthermore, this was not necessarily at the expense of responsivity or semantic contingency. The preference for instructional talk appeared to reflect deeply held cultural beliefs about the role of adults and children within the family and it is argued that the cultural paradigm is vitally important to consider when evaluating PCI. Given a potential risk that such young children may be vulnerable in terms of language difficulties, we offer an example of how PCI can be enhanced to encourage language development without disrupting the naturally occurring talk or the underlying purpose of the interaction

Periplasmic depolymerase provides insight into ABC transporter-dependent secretion of bacterial capsular polysaccharides

This work was supported in part by grants from the Canadian Institutes of Health Research (FDN_148364) (to C.W.). S.D.L. is a recipient of a Natural Science and Engineering Research Council Alexander Graham Bell Canada Graduate Scholarship and Michael Smith Foreign Study Supplement. C.W. is a Canada Research Chair. J.H.N. is a Wellcome Trust Investigator (100209/Z/12/Z).Capsules are surface layers of hydrated capsular polysaccharides (CPSs) produced by many bacteria. The human pathogen Salmonella enterica serovar Typhi produces "Vi antigen" CPS, which contributes to virulence. In a conserved strategy used by bacteria with diverse CPS structures, translocation of Vi antigen to the cell surface is driven by an ATP-binding cassette (ABC) transporter. These transporters are engaged in heterooligomeric complexes proposed to form an enclosed translocation conduit to the cell surface, allowing the transporter to power the entire process. We identified Vi antigen biosynthesis genetic loci in genera of the Burkholderiales, which are paradoxically distinguished from S. Typhi by encoding VexL, a predicted pectate lyase homolog. Biochemical analyses demonstrated that VexL is an unusual metal-independent endolyase with an acidic pH optimum that is specific for Oacetylated Vi antigen. A 1.22-Å crystal structure of the VexL-Vi antigen complex revealed features which distinguish common secreted catabolic pectate lyases from periplasmic VexL, which participates in cell-surface assembly. VexL possesses a right-handed parallel beta-superhelix, of which one face forms an electropositive glycan-binding groove with an extensive hydrogen bonding network that includes Vi antigen acetyl groups and confers substrate specificity. VexL provided a probe to interrogate conserved features of the ABC transporter-dependent export model. When introduced into S. Typhi, VexL localized to the periplasm and degraded Vi antigen. In contrast, a cytosolic derivative had no effect unless export was disrupted. These data provide evidence that CPS assembled in ABC transporter-dependent systems is actually exposed to the periplasm during envelope translocation.Publisher PDFPeer reviewe

Aquatic community response to volcanic eruptions on the Ecuadorian Andean flank: evidence from the palaeoecological record

Aquatic ecosystems in the tropical Andes are under increasing pressure from human modification of the landscape (deforestation and dams) and climatic change (increase of extreme events and 1.5 °C on average temperatures are projected for AD 2100). However, the resilience of these ecosystems to perturbations is poorly understood. Here we use a multi-proxy palaeoecological approach to assess the response of aquatic ecosystems to a major mechanism for natural disturbance, volcanic ash deposition. Specifically, we present data from two Neotropical lakes located on the eastern Andean flank of Ecuador. Laguna Pindo (1°27.132′S–78°04.847′W) is a tectonically formed closed basin surrounded by a dense mid-elevation forest, whereas Laguna Baños (0°19.328′S–78°09.175′W) is a glacially formed lake with an inflow and outflow in high Andean Páramo grasslands. In each lake we examined the dynamics of chironomids and other aquatic and semi-aquatic organisms to explore the effect of thick (> 5 cm) volcanic deposits on the aquatic communities in these two systems with different catchment features. In both lakes past volcanic ash deposition was evident from four large tephras dated to c.850 cal year BP (Pindo), and 4600, 3600 and 1500 cal year BP (Baños). Examination of the chironomid and aquatic assemblages before and after the ash depositions revealed no shift in composition at Pindo, but a major change at Baños occurred after the last event around 1500 cal year BP. Chironomids at Baños changed from an assemblage dominated by Pseudochironomus and Polypedilum nubifer-type to Cricotopus/Paratrichocladius type-II, and such a dominance lasted for approximately 380 years. We suggest that, despite potential changes in the water chemistry, the major effect on the chironomid community resulted from the thickness of the tephra being deposited, which acted to shallow the water body beyond a depth threshold. Changes in the aquatic flora and fauna at the base of the trophic chain can promote cascade effects that may deteriorate the ecosystem, especially when already influenced by human activities, such as deforestation and dams, which is frequent in the high Andes

Evidence- and consensus-based guidelines for drug-drug interactions with anticancer drugs:A practical and universal tool for management

Drug-drug interactions (DDIs) with anticancer drugs are common and can significantly affect efficacy and toxicity of treatment. Therefore, a Dutch Multidisciplinary Expert group is assessing the clinical signifi-cance of DDIs in oncology and provides recommendations for the management of these DDIs. We present an overview of methodology and outcome of an evidence-and consensus-based assessment of DDIs be-tween anticancer drugs and non-anticancer drugs.A literature search was performed through PubMed and EMA and FDA assessment reports, to iden-tify potential DDI's involving anticancer drugs. For each potential DDI a concept report for risk analysis and practical advice for management was created. Subsequently, this risk analysis and the corresponding advice were assessed and weighed.A total of 290 potential DDIs have been identified in the literature thus far. Of these 290 potential DDIs, the Expert Group has identified 94 (32%) DDIs as clinically relevant, with a need for an automated alert and a suggested intervention. Furthermore, 110 DDIs have been identified as clinically not relevant. For 86 potential DDIs evidence supporting a relevant DDI was insufficient and in these cases neither an alert nor advice regarding a suggested intervention were formulated.A transparent risk analysis is presented for identification of clinically relevant DDIs with anticancer drugs. Integration of DDI guidelines into the national electronic prescribing system is essential to achieve optimal efficacy and minimal toxicity in patients receiving anticancer therapy. A clear overview of clin-ically relevant DDIs with anticancer therapy provides clinicians with a structured, evidence-based and consensus-built tool for anticancer therapy surveillance. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Personalised Therapeutic

Optimal estimation of qubit states with continuous time measurements

We propose an adaptive, two steps strategy, for the estimation of mixed qubit states. We show that the strategy is optimal in a local minimax sense for the trace norm distance as well as other locally quadratic figures of merit. Local minimax optimality means that given $n$ identical qubits, there exists no estimator which can perform better than the proposed estimator on a neighborhood of size $n^{-1/2}$ of an arbitrary state. In particular, it is asymptotically Bayesian optimal for a large class of prior distributions. We present a physical implementation of the optimal estimation strategy based on continuous time measurements in a field that couples with the qubits. The crucial ingredient of the result is the concept of local asymptotic normality (or LAN) for qubits. This means that, for large $n$, the statistical model described by $n$ identically prepared qubits is locally equivalent to a model with only a classical Gaussian distribution and a Gaussian state of a quantum harmonic oscillator. The term `local' refers to a shrinking neighborhood around a fixed state $\rho_{0}$. An essential result is that the neighborhood radius can be chosen arbitrarily close to $n^{-1/4}$. This allows us to use a two steps procedure by which we first localize the state within a smaller neighborhood of radius $n^{-1/2+\epsilon}$, and then use LAN to perform optimal estimation.Comment: 32 pages, 3 figures, to appear in Commun. Math. Phy

Local industrial systems and the location of FDI in Italy

This article investigates the determinants of foreign direct investment (FDI)location across Italian provinces. Specifically it examines the relationship between industry- specific local industrial systems and the location of inward FDI. This extends previous analysis beyond the mere density of activity, to illustrate the importance of the specific nature of agglomerations in attracting inward investment. The article develops a model of FDI location choice using a unique FDI database stratified by industry and province. The results also suggest that the importance of agglomeration differs between industries, and offers some explanation for this

The relationship between eruptive activity, flank collapse, and sea level at volcanic islands: A long-term (>1 Ma) record offshore Montserrat, Lesser Antilles

Hole U1395B, drilled southeast of Montserrat during Integrated Ocean Drilling Program Expedition 340, provides a long (>1 Ma) and detailed record of eruptive and mass-wasting events (>130 discrete events). This record can be used to explore the temporal evolution in volcanic activity and landslides at an arc volcano. Analysis of tephra fall and volcaniclastic turbidite deposits in the drill cores reveals three heightened periods of volcanic activity on the island of Montserrat (?930 ka to ?900 ka, ?810 ka to ?760 ka, and ?190 ka to ?120 ka) that coincide with periods of increased volcano instability and mass-wasting. The youngest of these periods marks the peak in activity at the Soufrière Hills volcano. The largest flank collapse of this volcano (?130 ka) occurred towards the end of this period, and two younger landslides also occurred during a period of relatively elevated volcanism. These three landslides represent the only large (>0.3 km3) flank collapses of the Soufrière Hills edifice, and their timing also coincides with periods of rapid sea-level rise (>5 m/ka). Available age data from other island arc volcanoes suggests a general correlation between the timing of large landslides and periods of rapid sea-level rise, but this is not observed for volcanoes in intra-plate ocean settings. We thus infer that rapid sea-level rise may modulate the timing of collapse at island arc volcanoes, but not in larger ocean-island settings

Semiparametrically Efficient Inference Based on Signs and Ranks for Median Restricted Models

Since the pioneering work of Koenker and Bassett (1978), econometric models involving median and quantile rather than the classical mean or conditional mean concepts have attracted much interest.Contrary to the traditional models where the noise is assumed to have mean zero, median-restricted models enjoy a rich group-invariance structure.In this paper, we exploit this invariance structure in order to obtain semiparametrically efficient inference procedures for these models.These procedures are based on residual signs and ranks, and therefore insensitive to possible misspecification of the underlying innovation density, yet semiparametrically efficient at correctly specified densities.This latter combination is a definite advantage of these procedures over classical quasi-likelihood methods.The techniques we propose can be applied, without additional technical difficulties, to both cross-sectional and time-series models.They do not require any explicit tangent space calculation nor any projections on these.

Quantifying the intra-habitat variation of seagrass beds with unoccupied aerial vehicles (UAVs)

Accurate knowledge of the spatial extent of seagrass habitats is essential for monitoring and management purposes given their ecological and economic significance. Extent data are typically presented in binary (presence/absence) or arbitrary, semi-quantitative density bands derived from low-resolution satellite imagery, which cannot resolve fine-scale features and intra-habitat variability. Recent advances in consumer-grade unoccupied aerial vehicles (UAVs) have advanced our ability to survey large areas at higher resolution and at lower cost. This has improved the accessibility of mapping technologies to developing coastal nations, where a large proportion of the world’s seagrass habitats are found. Here, we present the application of UAV-gathered imagery to determine seagrass habitat extent and percent of canopy cover. Four contrasting sites were surveyed in the Turneffe Atoll Marine Reserve, Belize, and seagrass canopy cover was ground truthed from in situ quadrats. Orthomosaic images were created for each site from the UAV-gathered imagery. Three modelling techniques were tested to extrapolate the findings from quadrats to spatial information, producing binary (random forest) and canopy cover (random forest regression and beta regression) habitat maps. The most robust model (random forest regression) had an average absolute error of 6.8–11.9% (SE of 8.2–14), building upon previous attempts at mapping seagrass density from satellite imagery, which achieved errors between 15–20% approximately. The resulting maps exhibited great intra-habitat heterogeneity and different levels of patchiness, which were attributed to site energetics and, possibly, species composition. The extra information in the canopy cover maps provides greater detail and information for key management decisions and provides the basis for future spatial studies and monitoring programmes