On the Complexity of Counterfactual Reasoning

We study the computational complexity of counterfactual reasoning in relation to the complexity of associational and interventional reasoning on structural causal models (SCMs). We show that counterfactual reasoning is no harder than associational or interventional reasoning on fully specified SCMs in the context of two computational frameworks. The first framework is based on the notion of treewidth and includes the classical variable elimination and jointree algorithms. The second framework is based on the more recent and refined notion of causal treewidth which is directed towards models with functional dependencies such as SCMs. Our results are constructive and based on bounding the (causal) treewidth of twin networks -- used in standard counterfactual reasoning that contemplates two worlds, real and imaginary -- to the (causal) treewidth of the underlying SCM structure. In particular, we show that the latter (causal) treewidth is no more than twice the former plus one. Hence, if associational or interventional reasoning is tractable on a fully specified SCM then counterfactual reasoning is tractable too. We extend our results to general counterfactual reasoning that requires contemplating more than two worlds and discuss applications of our results to counterfactual reasoning with a partially specified SCM that is coupled with data. We finally present empirical results that measure the gap between the complexities of counterfactual reasoning and associational/interventional reasoning on random SCMs.Comment: An earlier version of this paper appeared in NeurIPS 2022 workshop, "A causal view on dynamical systems.

Advancing Transformer's Capabilities in Commonsense Reasoning

Recent advances in general purpose pre-trained language models have shown great potential in commonsense reasoning. However, current works still perform poorly on standard commonsense reasoning benchmarks including the Com2Sense Dataset. We argue that this is due to a disconnect with current cutting-edge machine learning methods. In this work, we aim to bridge the gap by introducing current ML-based methods to improve general purpose pre-trained language models in the task of commonsense reasoning. Specifically, we experiment with and systematically evaluate methods including knowledge transfer, model ensemble, and introducing an additional pairwise contrastive objective. Our best model outperforms the strongest previous works by ~15\% absolute gains in Pairwise Accuracy and ~8.7\% absolute gains in Standard Accuracy

Disinfection and Bactericidal Effect Using Photocatalytic Oxidation

This article first gives a brief review of the literature on disinfection and bactericidal effect using photocatalytic oxidation (PCO) technology. Photocatalytic chemistry of titanium dioxide has been extensively studied over the last 30 years for removal of organic and inorganic compounds from contaminated water and air. This review provides (1) background on PCO technology, (2) biological effect of PCO, (3) mechanism of cell and DNA damage photoinduced by PCO. Relevant research conducted in our laboratory is also presented. Finally, possible applications of the PCO for engineering controls of infectious diseases are discussed

Optimizing Management of the Qinling–Daba Mountain Area Based on Multi-Scale Ecosystem Service Supply and Demand

Accurately identifying the supply and demand of ecosystem services at multiple scales and determining the factors that influence the supply–demand relationship are crucial for guiding the sustainable management and restoration of regional ecosystem services. In view of this, we quantified the supply and demand of five ecosystem services at multiple scales in the Qinling–Daba Mountain area based on spatial and statistical data, exploring the relationships between the supply and demand for ecosystem services at multiple scales and examining the mechanisms by which factors like natural and human activities affect the evolution of the supply and demand patterns of these services. The results show that (1) there was no risk associated with supply and demand of ESs in the Qinling–Daba Mountain area, and numerous ESs were in excess. The impact of ES supply and demand became increasingly clear as the spatial scale was increased. (2) Under multiple spatial scales, the relationship between the supply and demand of ESs will change. At the mesoscale, the relationship between ES supply and demand was the most significant, whereas at the macroscale, the relationship between ES demands was the most significant. (3) Cultivated land, grass land, and forest land are the key land use categories in regional ecosystem service hotspots, providing richer ecosystem service functions for the region. (4) Precipitation and NDVI are the main elements determining the supply of ecosystem services. While GDP and population density have a significant impact on the demand for ecosystem services, natural causes are primarily responsible for trade-offs in ecosystem services. This study aims to evaluate the supply–demand relationship and driving factors of multiple scale in the Qinling–Daba Mountains, providing a scientific basis for the sustainable management of ecosystems in the region

Isolation and genetic characteristics of Novel H4N1 Avian Influenza viruses in ChongQing, China

Abstract Background Avian influenza viruses (AIVs) constitute significant zoonotic pathogens encompassing a broad spectrum of subtypes. Notably, the H4 subtype of AIVs has a pronounced ability to shift hosts. The escalating prevalence of the H4 subtype heightens the concern for its zoonotic potential, signaling an urgent need for vigilance. Methods During the period from December 2021 to November 2023, we collected AIV-related environmental samples and assessed them using a comprehensive protocol that included nucleic acid testing, gene sequencing, isolation culture, and resequencing. Results In this study, a total of 934 environmental samples were assessed, revealing a remarkably high detection rate (43.66%, 289/662) of AIV in the live poultry market. Notably, the H4N1 subtype AIV (cs2301) was isolated from the live poultry market and its complete genome sequence was successfully determined. Subsequent analysis revealed that cs2301, resulting from a reassortment event between wild and domesticated waterfowl, exhibits multiple mutations and demonstrates potential for host transfer. Conclusions Our research once again demonstrates the significant role of wild and domesticated waterfowl in the reassortment process of avian influenza virus, enriching the research on the H4 subtype of AIV, and emphasizing the importance of proactive monitoring the environment related to avian influenza virus

Additional file 1 of Serum lipidomic study of long-chain fatty acids in psoriasis patients prior to and after anti-IL-17A monoclonal antibody treatment by quantitative GC‒MS analysis with in situ extraction

Additional file 1: Table S1. Qualitative and quantitative ions of 14 LCFAs in SIM mode. Table S2. Concentrations (μM) of LCFAs in serum samples of healthy individuals and psoriasis patients receiving pretherapy and posttreatment with anti-IL-17A mAb. Table S3. Concentrations (μM) of LCFAs in serum samples of IMQ-treat WT and Tcrd-/- mice. Fig. S1. LCFAs derivatization method optimization. To achieve optimal efficiency, 30 μL LCFAs should be heated in the 500 μL 15% BF3-CH3OH solution (a-c) at 40°C for 30 minutes (d, e). Dichloromethane was also recommended as a superior extraction solvent (f). *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001. Fig. S2. Correlation analysis of serum ω-6 (a) and ω-3 (b) PUFAs with PASI scores in psoriasis patients. Fig. S3. LCFAs were conducted on ROC curve analysis. AUC values of 10 LCFAs in the PSV/HC (a) and W8/PSV (b) comparisons