Liver fibrosis MR images classification based on higher-order interaction and sample distribution rebalancing.

The fractal features of liver fibrosis MR images exhibit an irregular fragmented distribution, and the diffuse feature distribution lacks interconnectivity, result- ing in incomplete feature learning and poor recognition accuracy. In this paper, we insert recursive gated convolution into the ResNet18 network to introduce spatial information interactions during the feature learning process and extend it to higher orders using recursion. Higher-order spatial information interactions enhance the correlation between features and enable the neural network to focus more on the pixel-level dependencies, enabling a global interpretation of liver MR images. Additionally, the existence of light scattering and quantum noise during the imaging process, coupled with environmental factors such as breathing artifacts caused by long time breath holding, affects the quality of the MR images. To improve the classification performance of the neural network and better cap- ture sample features, we introduce the Adaptive Rebalance loss function and incorporate the feature paradigm as a learnable adaptive attribute into the angular margin auxiliary function. Adaptive Rebalance loss function can expand the inter-class distance and narrow the intra-class difference to further enhance discriminative ability of the model. We conduct extensive experiments on liver fibrosis MR imaging involving 209 patients. The results demonstrate an average improvement of two percent in recognition accuracy compared to ResNet18. The github is at https://github.com/XZN1233/paper.git.

A structured methodology to understand municipal waste generation at local level with minimized effort: development and case study.

Understanding municipal solid waste (MSW) generation is a key requirement for designing and optimizing MSW collection services. The present contribution proposes a statistical methodology to identify MSW generation patterns from MSW collection records. The methodology aims at finding statistically distinct household waste generation patterns within the days of the week and within months (seasonal variation). It is based on standard statistical methods (ANOVA complemented by non-parametric tests and cluster analysis). The methodology was applied to a Portuguese neighbourhood to assist in the definition of a waste sampling campaign to support the implementation of a pilot PAYT. The results showed the existence of groups with statistically distinct MSW generation patterns both at the weekly and monthly time scales. Three clusters of days of the week, with high, medium and low generation, and two clusters of months, with high and low generation, were identified. These results allowed to design and implement a customized field waste sampling campaign to estimate the MSW generated at the study site with minimal field work. Instead of implementing a homogeneous sampling campaign (equal number of samples for every day of the week and for every month), the samples were collected from the days and months that showed statistically distinct MSW generation pattern. The systematic procedure can be easily adapted to any given location, thus being a useful tool that combines statistical analysis with field collected data.

Low-cost multi-core inertial microfluidic centrifuge for high-throughput cell concentration.

We developed a low-cost multi-core inertial microfluidic centrifuge (IM-centrifuge) to achieve a continuous-flow cell/particle concentration at a throughput of up to 20 mL/min. To lower the cost of our IM-centrifuge, we clamped a disposable multilayer film-based inertial microfluidic (MFIM) chip with two reusable plastic housings. The key MFIM chip was fabricated in low-cost materials by stacking different polymer-film channel layers and double-sided tape. To increase processing throughput, multiplexing spiral inertial microfluidic channels were integrated within an all-in-one MFIM chip, and a novel sample distribution strategy was employed to equally distribute the sample into each channel layer. Then, we characterized the focusing performance in the MFIM chip over a wide flow-rate range. The experimental results showed that our IM-centrifuge was able to focus various-sized particles/cells to achieve volume reduction. The sample distribution strategy also effectively ensured identical focusing and concentration performances in different cores. Finally, our IM-centrifuge was successfully applied to concentrate microalgae cells with irregular shapes and highly polydisperse sizes. Thus, our IM-centrifuge holds the potential to be employed as a low-cost, high-throughput centrifuge for disposable use in low-resource settings.

Analysis of Pseudomonas aeruginosa in Children′s Hospital and Ward Disinfection and Isolation of Infected Patients / 中华医院感染学杂志

OBJECTIVE To understand the relationship between the detection rate of Pseudomonas aeruginosa in Children′s Hospital wards from Jan 2008 to Sep 2008 and disinfection and isolation in the department and investigate the change in antimierobial resistance of P.aeruginosa to provide basis for reasonable use of antibiotics in clinical practice.METHODS The clinically isolated P.aeruginosa strains were collected,cultured and identified by paper diffusing method.The results were evaluated according to the relevant documents of NCCLS of USA.RESULTS The resistant rates of P.aeruginosa to Ampicillin,Ampicillin/Sulbactam,ceftriaxone,cefazolin and SMI were higher than 98%.Their resistant rate to Levofloxacin and IMP was the lowest(about 2% or so).CONCLUSIONS Effective disinfection and isolation of P.aeruginosa should be performed.Selection of antimicrobial drugs should be according to the results of drug susceptibility,reduce the rate of bacterial resistance.