Thermoacoustic heat pump utilizing medium/low-grade heat sources for domestic building heating

Thermoacoustic heat pumps are a promising heating technology that utilizes medium/low-grade heat to reduce reliance on electricity. This study proposes a single direct-coupled configuration for a thermoacoustic heat pump, aimed at minimizing system complexity and making it suitable for domestic applications. Numerical investigations were conducted under typical household heating conditions, including performance analysis, exergy loss evaluation, and axial distribution of key parameters. Results show that the proposed thermoacoustic heat pump achieves a heating capacity of 5.7 kW and a coefficient of performance of 1.4, with a heating temperature of 300 °C and a heat-sink temperature of 55 °C. A comparison with existing absorption heat pumps reveals favorable adaptability for large temperature lift applications. A case study conducted in Finland over an annual cycle analyzes the economic and environmental performance of the system, identifying two distinct modes based on the driving heat source: medium temperature (≥250 °C) and low temperature (<250 °C), both of which exhibit favorable heating performance. When the thermoacoustic heat pump is driven by waste heat, energy savings of 20.1 MWh/year, emission reductions of 4143 kgCO$_2$/year, and total environmental cost savings of 1629 €/year are obtained. These results demonstrate the potential of the proposed thermoacoustic heat pump as a cost-effective and environmentally friendly option for domestic building heating using medium/low-grade heat sources

OccupancyDETR: Making Semantic Scene Completion as Straightforward as Object Detection

Visual-based 3D semantic occupancy perception (also known as 3D semantic scene completion) is a new perception paradigm for robotic applications like autonomous driving. Compared with Bird's Eye View (BEV) perception, it extends the vertical dimension, significantly enhancing the ability of robots to understand their surroundings. However, due to this very reason, the computational demand for current 3D semantic occupancy perception methods generally surpasses that of BEV perception methods and 2D perception methods. We propose a novel 3D semantic occupancy perception method, OccupancyDETR, which consists of a DETR-like object detection module and a 3D occupancy decoder module. The integration of object detection simplifies our method structurally - instead of predicting the semantics of each voxels, it identifies objects in the scene and their respective 3D occupancy grids. This speeds up our method, reduces required resources, and leverages object detection algorithm, giving our approach notable performance on small objects. We demonstrate the effectiveness of our proposed method on the SemanticKITTI dataset, showcasing an mIoU of 23 and a processing speed of 6 frames per second, thereby presenting a promising solution for real-time 3D semantic scene completion

Profiling users for question answering communities via flow-based constrained co-embedding model

In this article, we study the task of user profiling in question answering communities (QACs). Previous user profiling algorithms suffer from a number of defects: they regard users and words as atomic units, leading to the mismatch between them; they are designed for other applications but not for QACs; and some semantic profiling algorithms do not co-embed users and words, leading to making the affinity measurement between them difficult. To improve the profiling performance, we propose a neural Flow-based Constrained Co-embedding Model, abbreviated as FCCM. FCCM jointly co-embeds the vector representations of both users and words in QACs such that the affinities between them can be semantically measured. Specifically, FCCM extends the standard variational auto-encoder model to enforce the inferred embeddings of users and words subject to the voting constraint, i.e., given a question and the users who answer this question in the community, representations of the users whose answers receive more votes are closer to the representations of the words associated with these answers, compared with representations of whose receiving fewer votes. In addition, FCCM integrates normalizing flow into the variational auto-encoder framework to avoid the assumption that the distributions of the embeddings are Gaussian, making the inferred embeddings fit the real distributions of the data better. Experimental results on a Chinese Zhihu question answering dataset demonstrate the effectiveness of our proposed FCCM model for the task of user profiling in QACs

Sprachenlernen, Sprachpolitik, Sprache in den Medien und vieles mehr : Der Forschungsverbund „Educational Linguistics“ stellt sich vor

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The mediating effect of body mass index on the relationship between cigarette smoking and atopic sensitization in Chinese adults

Background: It is unclear whether the relationship between cigarette smoking and atopy is mediated by body fat mass, such as the Body Mass Index (BMI). We assessed the mediating role of BMI on the relationship between smoking and atopy in Chinese adults. Methods: A hospital-based case-control study of 786 atopic cases and 2771 controls was conducted in adults aged 18 years or older from March 2010 to September 2014 in Harbin, China. Mediation models were used to estimate the indirect effects of smoking on atopic sensitization through BMI. Results: Compared to non-smokers, light smokers and moderate smokers had a lower risk of inhalant allergen sensitization. The indirect effect of smoking and sensitization to aeroallergens were only observed in light smokers (point estimate, -0.026; 95% CI, -0.062 to -0.004). The mediating roles of BMI on the relationships between smoking and other types of allergic sensitization were not statistically significant. Conclusion: BMI appeared to partially mediate the effect of light smoking on sensitization to aeroallergens. However, considering the other harmful health effects of cigarette smoking, the effective method to lower the incidence of atopy would be to decrease body fat mass by physical exercise and employing other more healthy ways of living rather than smoking

Transcriptomic analysis identified SLC40A1 as a key iron metabolism-related gene in airway macrophages in childhood allergic asthma

Introduction: Asthma is the most common chronic condition in children, with allergic asthma being the most common phenotype, accounting for approximately 80% of cases. Growing evidence suggests that disruption of iron homeostasis and iron regulatory molecules may be associated with childhood allergic asthma. However, the underlying molecular mechanism remains unclear.Methods: Three childhood asthma gene expression datasets were analyzed to detect aberrant expression profiles of iron metabolism-related genes in the airways of children with allergic asthma. Common iron metabolism-related differentially expressed genes (DEGs) across the three datasets were identified and were subjected to functional enrichment analysis. Possible correlations between key iron metabolism-related DEGs and type 2 airway inflammatory genes were investigated. Single-cell transcriptome analysis further identified major airway cell subpopulations driving key gene expression. Key iron metabolism-related gene SLC40A1 was validated in bronchoalveolar lavage (BAL) cells from childhood asthmatics with control individuals by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunofluorescence. The intracellular iron content in BAL cells was assessed by Perls iron staining and the iron levels in BAL supernatant was measured by iron assay to assess airway iron metabolism status in childhood asthmatics.Results: Five common iron metabolism-related DEGs were identified, which were functionally related to iron homeostasis. Among these genes, downregulated SLC40A1 was strongly correlated with type 2 airway inflammatory markers and the gene signature of SLC40A1 could potentially be used to determine type 2-high and type 2-low subsets in childhood allergic asthmatics. Further single-cell transcriptomic analysis identified airway macrophages driving SLC40A1 expression. Immunofluorescence staining revealed colocalization of FPN (encoded by SLC40A1) and macrophage marker CD68. Down-regulation of SLC40A1 (FPN) was validated by qRT-PCR and immunofluorescence analysis. Results further indicated reduced iron levels in the BAL fluid, but increased iron accumulation in BAL cells in childhood allergic asthma patients. Furthermore, decreased expression of SLC40A1 was closely correlated with reduced iron levels in the airways of children with allergic asthma.Discussion: Overall, these findings reveal the potential role of the iron metabolism-related gene SLC40A1 in the pathogenesis of childhood allergic asthma