Application of PTR-MS for optimization of odour removal from intensive pig production with emphasis on biofiltration

Odour emission from intensive livestock production is becoming a nuisance to neighbors. Biofiltration is the most cost-effective technology for odor reduction. In this PhD study, PTR-MS was demonstrated to be a unique tool both for online evaluation of odor removal and for estimation of key parameters in biofiltration process. Kinetic study indicated the removal of odor is related both to mass load of the odorants and the air loading rate. Partition coefficients of sulfur compounds in biotrickling filter liquids were found to be generally very close to the corresponding partition coefficients in deionized water. Mass transfer coefficients of sulfur compounds in the biofilter packing media were determined through an established method based on breakthrough curves measured by PTR-MS

Zero-Shot Video Moment Retrieval from Frozen Vision-Language Models

Accurate video moment retrieval (VMR) requires universal visual-textual correlations that can handle unknown vocabulary and unseen scenes. However, the learned correlations are likely either biased when derived from a limited amount of moment-text data which is hard to scale up because of the prohibitive annotation cost (fully-supervised), or unreliable when only the video-text pairwise relationships are available without fine-grained temporal annotations (weakly-supervised). Recently, the vision-language models (VLM) demonstrate a new transfer learning paradigm to benefit different vision tasks through the universal visual-textual correlations derived from large-scale vision-language pairwise web data, which has also shown benefits to VMR by fine-tuning in the target domains. In this work, we propose a zero-shot method for adapting generalisable visual-textual priors from arbitrary VLM to facilitate moment-text alignment, without the need for accessing the VMR data. To this end, we devise a conditional feature refinement module to generate boundary-aware visual features conditioned on text queries to enable better moment boundary understanding. Additionally, we design a bottom-up proposal generation strategy that mitigates the impact of domain discrepancies and breaks down complex-query retrieval tasks into individual action retrievals, thereby maximizing the benefits of VLM. Extensive experiments conducted on three VMR benchmark datasets demonstrate the notable performance advantages of our zero-shot algorithm, especially in the novel-word and novel-location out-of-distribution setups.Comment: Accepted by WACV 202

Towards Generalisable Video Moment Retrieval: Visual-Dynamic Injection to Image-Text Pre-Training

The correlation between the vision and text is essential for video moment retrieval (VMR), however, existing methods heavily rely on separate pre-training feature extractors for visual and textual understanding. Without sufficient temporal boundary annotations, it is non-trivial to learn universal video-text alignments. In this work, we explore multi-modal correlations derived from large-scale image-text data to facilitate generalisable VMR. To address the limitations of image-text pre-training models on capturing the video changes, we propose a generic method, referred to as Visual-Dynamic Injection (VDI), to empower the model's understanding of video moments. Whilst existing VMR methods are focusing on building temporal-aware video features, being aware of the text descriptions about the temporal changes is also critical but originally overlooked in pre-training by matching static images with sentences. Therefore, we extract visual context and spatial dynamic information from video frames and explicitly enforce their alignments with the phrases describing video changes (e.g. verb). By doing so, the potentially relevant visual and motion patterns in videos are encoded in the corresponding text embeddings (injected) so to enable more accurate video-text alignments. We conduct extensive experiments on two VMR benchmark datasets (Charades-STA and ActivityNet-Captions) and achieve state-of-the-art performances. Especially, VDI yields notable advantages when being tested on the out-of-distribution splits where the testing samples involve novel scenes and vocabulary.Comment: CVPR202

PILRA is associated with immune cells infiltration in atrial fibrillation based on bioinformatics and experiment validation

Background and aimsinflammation plays an important role in atrial fibrillation (AF). In this study, we investigated the significance of immune cell infiltration in AF and identified the potential Hub genes involved in the regulation of immune cell infiltration in AF.Methodswe obtained AF datasets from the GEO database and analyzed them for obtaining differentially expressed genes (DEGs) by R software. Then, we performed GO, KEGG, and GSEA enrichment analyses of DEGs. The Hub genes of AF were determined by least absolute shrinkage selection operator (LASSO) regression analysis and weighted gene co-expression network analysis (WGCNA). Their validation was verified by using quantitative polymerase chain reaction (qPCR) in the AF rat model. Finally, we used a single sample GSEA (ssGSEA) to analyze immune cell infiltration and its relationship with hub genes.ResultsWe obtained 298 DGEs from the heatmap and found that DGEs were closely related to inflammation, immunity, and cytokine interactions by enrichment analyses. We obtained 10 co-expression modules by WGCNA. Among them, the module including CLEC4A, COTL1, EVI2B, FCER1G, GAPT, HCST, NCF2, PILRA, TLR8, and TYROBP had the highest correlation with AF. Four Hub genes (PILRA, NCF2, EVI2B, GAPT) were obtained further by LASSO analysis. The results suggested that the expression level of PILRA was significantly elevated in the rats with AF by qPCR, compared to the rats without AF. The results revealed that the infiltration of neutrophils, macrophages, monocytes, mast cells, immature B cells, myeloid-derived suppressor cell (MDSC), dendritic cell, and T cells and their partial subpopulations were closely related to AF by ssGSEA analysis, and PILRA was positively correlated with immature B cell, monocyte, macrophage, mast cell, dendritic cell, and T cells and their partial subpopulations by Spearman correlation analysis.ConclusionsPILRA was closely related to multiple types of immune cell infiltration, which may be associated with AF. PILRA may be a novel target of intervention for AF

Summary and Overview of the Odour Regulations Worldwide

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarise odour legislation in selected European countries (France, Germany, Austria, Hungary, the UK, Spain, the Netherlands, Italy, Belgium), North America (the USA and Canada), and South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces, and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modelling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application

Dynamic Complexity of a Phytoplankton-Fish Model with the Impulsive Feedback Control by means of Poincaré Map

The phytoplankton-fish model for catching fish with impulsive feedback control is established in this paper. Firstly, the Poincaré map for the phytoplankton-fish model is defined, and the properties of monotonicity, continuity, differentiability, and fixed point of Poincaré map are analyzed. In particular, the continuous and discontinuous properties of Poincaré map under different conditions are discussed. Secondly, we conduct the analysis of the necessary and sufficient conditions for the existence, uniqueness, and global stability of the order-1 periodic solution of the phytoplankton-fish model and obtain the sufficient conditions for the existence of the order-kk≥2 periodic solution of the system. Numerical simulation shows the correctness of our results which show that phytoplankton and fish with the impulsive feedback control can live stably under certain conditions, and the results have certain reference value for the dynamic change of phytoplankton in aquatic ecosystems