Membrane development for metal ions and anions separation

Master'sMASTER OF ENGINEERIN

Micro-optical Tandem Luminescent Solar Concentrators

Traditional concentrating photovoltaic (CPV) systems utilize multijunction cells to minimize thermalization losses, but cannot efficiently capture diffuse sunlight, which contributes to a high levelized cost of energy (LCOE) and limits their use to geographical regions with high direct sunlight insolation. Luminescent solar concentrators (LSCs) harness light generated by luminophores embedded in a light-trapping waveguide to concentrate light onto smaller cells. LSCs can absorb both direct and diffuse sunlight, and thus can operate as flat plate receivers at a fixed tilt and with a conventional module form factor. However, current LSCs experience significant power loss through parasitic luminophore absorption and incomplete light trapping by the optical waveguide. Here we introduce a tandem LSC device architecture that overcomes both of these limitations, consisting of a PLMA polymer layer with embedded CdSe/CdS quantum dot (QD) luminophores and InGaP micro-cells, which serve as a high bandgap absorber on top of a conventional Si photovoltaic. We experimentally synthesize CdSe/CdS QDs with exceptionally high quantum-yield (99%) and ultra-narrowband emission optimally matched to fabricated III-V InGaP micro-cells. Using a Monte Carlo ray-tracing model, we show the radiative limit power conversion efficiency for a module with these components to be 30.8% diffuse sunlight conditions. These results indicate that a tandem LSC-on-Si architecture could significantly improve upon the efficiency of a conventional Si photovoltaic module with simple and straightforward alterations of the module lamination steps of a Si photovoltaic manufacturing process, with promise for widespread module deployment across diverse geographical regions and energy markets

Clustering of sedentary behaviours, physical activity, and energy-dense food intake in six-year-old children

This study examined the clustering of lifestyle behaviours in children aged six years from a prospective cohort study in the Netherlands. Additionally, we analysed the associations between socioeconomic status and the lifestyle behaviour clusters that we identified. Data of 4059 children from the Generation R Study were analysed. Socioeconomic status was measured by maternal educational level and net household income. Lifestyle behaviours including screen time, physical activity, calorie-rich snack consumption and sugar-sweetened beverages consumption were measured via a parental questionnaire. Hierarchical and non-hierarchical cluster analyses were applied. The associations between socioeconomic status and lifestyle behaviour clusters were assessed using logistic regression models. Three lifestyle clusters were identified: “relatively healthy lifestyle” cluster (n = 1444), “high screen time and physically inactive” cluster (n = 1217), and “physically active, high snacks and sugary drinks” cluster (n = 1398). Children from high educated mothers or high-income households were more likely to be allocated to the “relatively healthy lifestyle” cluster, while children from low educated mothers or from low-income households were more likely to be allocated in the “high screen time and physically inactive” cluster. Intervention development and prevention strategies may use this information to further target programs promoting healthy behaviours of children and their families

Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning

Depth-aware panoptic segmentation is an emerging topic in computer vision which combines semantic and geometric understanding for more robust scene interpretation. Recent works pursue unified frameworks to tackle this challenge but mostly still treat it as two individual learning tasks, which limits their potential for exploring cross-domain information. We propose a deeply unified framework for depth-aware panoptic segmentation, which performs joint segmentation and depth estimation both in a per-segment manner with identical object queries. To narrow the gap between the two tasks, we further design a geometric query enhancement method, which is able to integrate scene geometry into object queries using latent representations. In addition, we propose a bi-directional guidance learning approach to facilitate cross-task feature learning by taking advantage of their mutual relations. Our method sets the new state of the art for depth-aware panoptic segmentation on both Cityscapes-DVPS and SemKITTI-DVPS datasets. Moreover, our guidance learning approach is shown to deliver performance improvement even under incomplete supervision labels.Comment: to be published in ICCV 202

PACE Solver Description: Hust-Solver - A Heuristic Algorithm of Directed Feedback Vertex Set Problem

A directed graph is formed by vertices and arcs from one vertex to another. The feedback vertex set problem (FVSP) consists in making a given directed graph acyclic by removing as few vertices as possible. In this write-up, we outline the core techniques used in the heuristic feedback vertex set algorithm, submitted to the heuristic track of the 2022 PACE challenge

Activation of the IL-23/Th17 Axis

The aim of this paper is to determine the modulatory effects of Lactobacillus acidophilus on the IL-23/Th17 immune axis in experimental colitis. DSS-induced mouse models of UC were to be saline, hormones, and different concentrations of Lactobacillus acidophilus intervention. The expression of interleukin-(IL-) 17, tumor necrosis factor (TNF ), IL-23, transforming growth factor 1 (TGF 1), signal transducer and activator of transcription 3 (STAT3), and phosphorylated (p)-STAT3 was examined by RT-PCR, Western blotting, and immunohistochemical analysis. And the results showed that administration of L. acidophilus suppressed Th17 cell-mediated secretion of proinflammatory cytokine IL-17 through downregulation of IL-23 and TGF 1 expression and downstream phosphorylation of p-STAT3

Ethnic background and children’s television viewing trajectories

This study, conducted in the Netherlands, evaluated the association between ethnic background and children’s TV viewing time at multiple time points and its trajectory. We analyzed 4,833 children with a Dutch, Moroccan, Turkish, or Surinamese ethnic background from the Generation R Study, a population-based study in the Netherlands. Parent-reported television viewing time for children at ages 2, 3, 4, 6, and 9 years was collected by questionnaires sent from April 2004 until January 2015. Odds ratios of watching television 1 hour/day at each age were calculated for children from the various ethnic backgrounds. Generalized logistic mixed models (GLMMs) were used to assess the association between ethnic background and television viewing time trajectory. The effect modification by family socioeconomic status was examined in cross-sectional and longitudinal analyses. The percentage of children viewing television 1 hour/day increased from age 2 to 9 years for children from all ethnic backgrounds. After adjusting for maternal educational level and net household income, children from all ethnic subgroups had greater odds of watching television 1 hour/ day at some time points compared with children with a Dutch background (Surinamese: all ages; Moroccan: at ages 4 and 6 years; Turkish: at ages 4 and 9 years). The GLMMs indicated that television viewing trajectories differed between ethnic subgroups. The associations between ethnic background and children’s television viewing time were moderated by maternal educational level for child ages 4 and 6 years (p < 0.05). In longitudinal analyses, the ethnic differences in probability of watching television 1 hour/day were larger in children from high-educated mothers than in children from low-educated mothers. In conclusion, ethnic differences in television viewing time were present at all measuring time points. The discrepancy between children with a Dutch background and children with another background was larger in high maternal educational subgroups

Relationship between socioeconomic status and weight gain during infancy: The BeeBOFT study

Background Increased weight gain during infancy is a risk factor for obesity and related diseases in later life. The aim of the present study was to investigat