Do topical repellents divert mosquitoes within a community? Health equity implications of topical repellents as a mosquito bite prevention tool.

OBJECTIVES: Repellents do not kill mosquitoes--they simply reduce human-vector contact. Thus it is possible that individuals who do not use repellents but dwell close to repellent users experience more bites than otherwise. The objective of this study was to measure if diversion occurs from households that use repellents to those that do not use repellents. METHODS: The study was performed in three Tanzanian villages using 15%-DEET and placebo lotions. All households were given LLINs. Three coverage scenarios were investigated: complete coverage (all households were given 15%-DEET), incomplete coverage (80% of households were given 15%-DEET and 20% placebo) and no coverage (all households were given placebo). A crossover study design was used and coverage scenarios were rotated weekly over a period of ten weeks. The placebo lotion was randomly allocated to households in the incomplete coverage scenario. The level of compliance was reported to be close to 100%. Mosquito densities were measured through aspiration of resting mosquitoes. Data were analysed using negative binomial regression models. FINDINGS: Repellent-users had consistently fewer mosquitoes in their dwellings. In villages where everybody had been given 15%-DEET, resting mosquito densities were fewer than half that of households in the no coverage scenario (Incidence Rate Ratio [IRR]=0.39 (95% confidence interval [CI]: 0.25-0.60); p<0.001). Placebo-users living in a village where 80% of the households used 15%-DEET were likely to have over four-times more mosquitoes (IRR=4.17; 95% CI: 3.08-5.65; p<0.001) resting in their dwellings in comparison to households in a village where nobody uses repellent. CONCLUSIONS: There is evidence that high coverage of repellent use could significantly reduce man-vector contact but with incomplete coverage evidence suggests that mosquitoes are diverted from households that use repellent to those that do not. Therefore, if repellents are to be considered for vector control, strategies to maximise coverage are required

Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration

Convolutional neural networks (CNNs) have recently led to significant advances in automatic segmentations of anatomical structures in medical images, and a wide variety of network architectures are now available to the research community. For applications such as segmentation of the prostate in magnetic resonance images (MRI), the results of the PROMISE12 online algorithm evaluation platform have demonstrated differences between the best-performing segmentation algorithms in terms of numerical accuracy using standard metrics such as the Dice score and boundary distance. These small differences in the segmented regions/boundaries outputted by different algorithms may potentially have an unsubstantial impact on the results of downstream image analysis tasks, such as estimating organ volume and multimodal image registration, which inform clinical decisions. This impact has not been previously investigated. In this work, we quantified the accuracy of six different CNNs in segmenting the prostate in 3D patient T2-weighted MRI scans and compared the accuracy of organ volume estimation and MRI-ultrasound (US) registration errors using the prostate segmentations produced by different networks. Networks were trained and tested using a set of 232 patient MRIs with labels provided by experienced clinicians. A statistically significant difference was found among the Dice scores and boundary distances produced by these networks in a non-parametric analysis of variance (p < 0.001 and p < 0.001, respectively), where the following multiple comparison tests revealed that the statistically significant difference in segmentation errors were caused by at least one tested network. Gland volume errors (GVEs) and target registration errors (TREs) were then estimated using the CNN-generated segmentations. Interestingly, there was no statistical difference found in either GVEs or TREs among different networks, (p = 0.34 and p = 0.26, respectively). This result provides a real-world example that these networks with different segmentation performances may potentially provide indistinguishably adequate registration accuracies to assist prostate cancer imaging applications. We conclude by recommending that the differences in the accuracy of downstream image analysis tasks that make use of data output by automatic segmentation methods, such as CNNs, within a clinical pipeline should be taken into account when selecting between different network architectures, in addition to reporting the segmentation accuracy

Optimisation of CH4 and CO2 conversion and selectivity of H2 and CO for the dry reforming of methane by a microwave plasma technique using a Box–Behnken design

A microwave plasma was generated by N2 gas. Synthesis gases (H2 and CO) were produced by the interaction of CH4 and CO2 under plasma conditions at atmospheric pressure. The experimental pilot plant was set up, and the gases were sampled and analysed by gas chromatography–mass spectrometry. The Box–Behnken design (BBD) method was used to find the optimising conditions based on the experimental results. The response surface methodology based on a three-parameter and three-level BBD has been developed to find the effects of independent process parameters, which were represented by the gas flow rates of CH4, CO2, and N2 and their effects on the process performance in terms of CH4, CO2, and N2 conversion and selectivity of H2 and CO. In this work, four models based on quadratic polynomial regression have been determined to understand the connection between the limits of the feed gas flow rate and the performance of the process. The results show that the most important factor influencing the CO2, CH4, and N2 conversion and the selectivity of H2 and CO was “CO2 feed gas flow rate.” At the maximum desirable value of 0.92, the optimum CH4, CO2, and N2 conversion were 84.91%, 44.40%, and 3.37%, respectively, and the selectivities of H2 and CO were 51.31% and 61.17%, respectively. This was achieved at a gas feed flow rate of 0.19, 0.38, and 1.49 L min-1 for CH4, CO2, and N2, respectively

On the crossing relation in the presence of defects

The OPE of local operators in the presence of defect lines is considered both in the rational CFT and the $c>25$ Virasoro (Liouville) theory. The duality transformation of the 4-point function with inserted defect operators is explicitly computed. The two channels of the correlator reproduce the expectation values of the Wilson and 't Hooft operators, recently discussed in Liouville theory in relation to the AGT conjecture.Comment: TEX file with harvmac; v3: JHEP versio

Ecology of a North Sea pockmark with an active methane seep

ABSTRACT: At a large North Sea pockmark, with active methane seeps, surface sediments were found to have higher insoluble sulphide concentrations than sedlments from the surrounding area. The fauna of the pockmark was characterized by 2 species which have not pi-evlously been reported from the Fladen Ground in the northern North Sea. These species were a b~valve, Thyasira sarsi (which is known to contain endosymbiotic sulphur-oxidising bacteria) and a mouthless and gutless nematode, Astomonerna sp., which also contains endosymbiotic bacteria The nematode was the dominant meiofauna species in the pockmark sediments. Both macro-lnfauna and total nematodes were in low abundance in samples taken from the base of the pockmark. Sediment samples from the pockmark contained numerous otoliths, implying that substantial winnowing of the sediment had taken place. This was supported by studies on the sulphide concentrations in the sediment which showed multiple layering of the sediments on the sides of the pockmark, suggesting displacement. The carbon isotope compositions (6I3c) of the tissues of benthic animals from in and around the pockmark were generally in the range -16 to -2O%, indicating that little methane-derived carbon was contributing to their nutrition. T sarsi had the most 13c-depleted tissues, -31.4 to -35.1 L, confirming the nutritional dependence of this species on chemoautotrophic bacteria that utilize reduced sulphur

Longitudinal Numbers-Needed-To-Treat (NNT) for Achieving Various Levels of Analgesic Response and Improvement with Etoricoxib, Naproxen, and Placebo in Ankylosing Spondylitis

<p>Abstract</p> <p>Background</p> <p>Clinical analgesic trials typically report response as group mean results. However, research has shown that few patients are average and most have responses at the extremes. Moreover, group mean results do not convey response levels and thus have limited value in representing the benefit-risk at an individual level. Responder analyses and numbers-needed-to-treat (NNT) are considered more relevant for evaluating treatment response. We evaluated levels of analgesic response and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score improvement and the associated NNTs.</p> <p>Methods</p> <p>This was a post-hoc analysis of a 6-week, randomized, double-blind study (N = 387) comparing etoricoxib 90 mg, etoricoxib 120 mg, naproxen 1000 mg, and placebo in AS. Spine pain and BASDAI were measured on a 100-mm visual analog scale. The number and percentage of patients achieving ≥30% and ≥50% improvement in both BASDAI and spine pain were calculated and used to determine the corresponding NNTs. Patients who discontinued from the study for any reason were assigned zero improvement beyond 7 days of the time of discontinuation.</p> <p>Results</p> <p>For etoricoxib 90 mg, etoricoxib 120 mg and naproxen 1000 mg, the NNTs at 6 weeks compared with placebo were 2.0, 2.0, and 2.7 respectively for BASDAI ≥30% improvement, and 3.2, 2.8, and 4.1 for ≥50% improvement. For spine pain, the NNTs were 1.9, 2.0, and 3.2, respectively, for ≥30% improvement, and 2.7, 2.5, and 3.7 for ≥50% improvement. The differences between etoricoxib and naproxen exceeded the limit of ±0.5 units described as a clinically meaningful difference for pain. Response rates and NNTs were generally similar and stable over 2, 4, and 6 weeks.</p> <p>Conclusions</p> <p>For every 2 patients treated with etoricoxib, 1 achieved a clinically meaningful (≥30%) improvement in spine pain and BASDAI beyond that expected from placebo, whereas the corresponding values were approximately 1 in every 3 patients treated with naproxen. Use of NNTs and responder analyses provide additional, complementary information beyond population mean responses when assessing efficacy compared to placebo and amongst active therapies.</p

Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation

Organ morphology is a key indicator for prostate disease diagnosis and prognosis. For instance, In longitudinal study of prostate cancer patients under active surveillance, the volume, boundary smoothness and their changes are closely monitored on time-series MR image data. In this paper, we describe a new framework for forecasting prostate morphological changes, as the ability to detect such changes earlier than what is currently possible may enable timely treatment or avoiding unnecessary confirmatory biopsies. In this work, an efficient feature-based MR image registration is first developed to align delineated prostate gland capsules to quantify the morphological changes using the inferred dense displacement fields (DDFs). We then propose to use kernel density estimation (KDE) of the probability density of the DDFrepresented future morphology changes, between current and future time points, before the future data become available. The KDE utilises a novel distance function that takes into account morphology, stage-of-progression and duration-ofchange, which are considered factors in such subject-specific forecasting. We validate the proposed approach on image masks unseen to registration network training, without using any data acquired at the future target time points. The experiment results are presented on a longitudinal data set with 331 images from 73 patients, yielding an average Dice score of 0.865 on a holdout set, between the ground-truth and the image masks warped by the KDE-predicted-DDFs

Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases.

BACKGROUND: Failure to keep outpatient medical appointments results in inefficiencies and costs. The objective of this study is to show the factors in an existing electronic database that affect failed appointments and to develop a predictive probability model to increase the effectiveness of interventions. METHODS: A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment. RESULTS: Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%. CONCLUSION: A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic

Coexistence of the topological state and a two-dimensional electron gas on the surface of Bi2Se3

Topological insulators are a recently discovered class of materials with fascinating properties: While the inside of the solid is insulating, fundamental symmetry considerations require the surfaces to be metallic. The metallic surface states show an unconventional spin texture, electron dynamics and stability. Recently, surfaces with only a single Dirac cone dispersion have received particular attention. These are predicted to play host to a number of novel physical phenomena such as Majorana fermions, magnetic monopoles and unconventional superconductivity. Such effects will mostly occur when the topological surface state lies in close proximity to a magnetic or electric field, a (superconducting) metal, or if the material is in a confined geometry. Here we show that a band bending near to the surface of the topological insulator Bi$_2$Se$_3$ gives rise to the formation of a two-dimensional electron gas (2DEG). The 2DEG, renowned from semiconductor surfaces and interfaces where it forms the basis of the integer and fractional quantum Hall effects, two-dimensional superconductivity, and a plethora of practical applications, coexists with the topological surface state in Bi$_2$Se$_3$. This leads to the unique situation where a topological and a non-topological, easily tunable and potentially superconducting, metallic state are confined to the same region of space.Comment: 12 pages, 3 figure

From Rotating Atomic Rings to Quantum Hall States

Considerable efforts are currently devoted to the preparation of ultracold neutral atoms in the emblematic strongly correlated quantum Hall regime. The routes followed so far essentially rely on thermodynamics, i.e. imposing the proper Hamiltonian and cooling the system towards its ground state. In rapidly rotating 2D harmonic traps the role of the transverse magnetic field is played by the angular velocity. For particle numbers significantly larger than unity, the required angular momentum is very large and it can be obtained only for spinning frequencies extremely near to the deconfinement limit; consequently, the required control on experimental parameters turns out to be far too stringent. Here we propose to follow instead a dynamic path starting from the gas confined in a rotating ring. The large moment of inertia of the fluid facilitates the access to states with a large angular momentum, corresponding to a giant vortex. The initial ring-shaped trapping potential is then adiabatically transformed into a harmonic confinement, which brings the interacting atomic gas in the desired quantum Hall regime. We provide clear numerical evidence that for a relatively broad range of initial angular frequencies, the giant vortex state is adiabatically connected to the bosonic $\nu=1/2$ Laughlin state, and we discuss the scaling to many particles.Comment: 9 pages, 5 figure