Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series

Learning directed acyclic graphs (DAGs) to identify causal relations underlying observational data is crucial but also poses significant challenges. Recently, topology-based methods have emerged as a two-step approach to discovering DAGs by first learning the topological ordering of variables and then eliminating redundant edges, while ensuring that the graph remains acyclic. However, one limitation is that these methods would generate numerous spurious edges that require subsequent pruning. To overcome this limitation, in this paper, we propose an improvement to topology-based methods by introducing limited time series data, consisting of only two cross-sectional records that need not be adjacent in time and are subject to flexible timing. By incorporating conditional instrumental variables as exogenous interventions, we aim to identify descendant nodes for each variable. Following this line, we propose a hierarchical topological ordering algorithm with conditional independence test (HT-CIT), which enables the efficient learning of sparse DAGs with a smaller search space compared to other popular approaches. The HT-CIT algorithm greatly reduces the number of edges that need to be pruned. Empirical results from synthetic and real-world datasets demonstrate the superiority of the proposed HT-CIT algorithm

Soil Organic Carbon Content and Microbial Functional Diversity Were Lower in Monospecific Chinese Hickory Stands than in Natural Chinese Hickory–Broad-Leaved Mixed Forests

To assess the effects of long-term intensive management on soil carbon cycle and microbial functional diversity, we sampled soil in Chinese hickory (Carya cathayensis Sarg.) stands managed intensively for 5, 10, 15, and 20 years, and in reference Chinese hickory–broad-leaved mixed forest (NMF) stands. We analyzed soil total organic carbon (TOC), microbial biomass carbon (MBC), and water-soluble organic carbon (WSOC) contents, applied 13C-nuclear magnetic resonance analysis for structural analysis, and determined microbial carbon source usage. TOC, MBC, and WSOC contents and the MBC to TOC ratios were lower in the intensively managed stands than in the NMF stands. The organic carbon pool in the stands managed intensively for twenty years was more stable, indicating that the easily degraded compounds had been decomposed. Diversity and evenness in carbon source usage by the microbial communities were lower in the stands managed intensively for 15 and 20 years. Based on carbon source usage, the longer the management time, the less similar the samples from the monospecific Chinese hickory stands were with the NMF samples, indicating that the microbial community compositions became more different with increased management time. The results call for changes in the management of the hickory stands to increase the soil carbon content and restore microbial diversity

Soil Organic Carbon Content and Microbial Functional Diversity Were Lower in Monospecific Chinese Hickory Stands than in Natural Chinese Hickory–Broad-Leaved Mixed Forests

To assess the effects of long-term intensive management on soil carbon cycle and microbial functional diversity, we sampled soil in Chinese hickory (Carya cathayensis Sarg.) stands managed intensively for 5, 10, 15, and 20 years, and in reference Chinese hickory–broad-leaved mixed forest (NMF) stands. We analyzed soil total organic carbon (TOC), microbial biomass carbon (MBC), and water-soluble organic carbon (WSOC) contents, applied 13C-nuclear magnetic resonance analysis for structural analysis, and determined microbial carbon source usage. TOC, MBC, and WSOC contents and the MBC to TOC ratios were lower in the intensively managed stands than in the NMF stands. The organic carbon pool in the stands managed intensively for twenty years was more stable, indicating that the easily degraded compounds had been decomposed. Diversity and evenness in carbon source usage by the microbial communities were lower in the stands managed intensively for 15 and 20 years. Based on carbon source usage, the longer the management time, the less similar the samples from the monospecific Chinese hickory stands were with the NMF samples, indicating that the microbial community compositions became more different with increased management time. The results call for changes in the management of the hickory stands to increase the soil carbon content and restore microbial diversity

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization

Domain generalization (DG) is a prevalent problem in real-world applications, which aims to train well-generalized models for unseen target domains by utilizing several source domains. Since domain labels, i.e., which domain each data point is sampled from, naturally exist, most DG algorithms treat them as a kind of supervision information to improve the generalization performance. However, the original domain labels may not be the optimal supervision signal due to the lack of domain heterogeneity, i.e., the diversity among domains. For example, a sample in one domain may be closer to another domain, its original label thus can be the noise to disturb the generalization learning. Although some methods try to solve it by re-dividing domains and applying the newly generated dividing pattern, the pattern they choose may not be the most heterogeneous due to the lack of the metric for heterogeneity. In this paper, we point out that domain heterogeneity mainly lies in variant features under the invariant learning framework. With contrastive learning, we propose a learning potential-guided metric for domain heterogeneity by promoting learning variant features. Then we notice the differences between seeking variance-based heterogeneity and training invariance-based generalizable model. We thus propose a novel method called Heterogeneity-based Two-stage Contrastive Learning (HTCL) for the DG task. In the first stage, we generate the most heterogeneous dividing pattern with our contrastive metric. In the second stage, we employ an invariance-aimed contrastive learning by re-building pairs with the stable relation hinted by domains and classes, which better utilizes generated domain labels for generalization learning. Extensive experiments show HTCL better digs heterogeneity and yields great generalization performance.Comment: This paper has been accepted by KDD 202

Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures

High-entropy alloys are an intriguing new class of metallic materials that derive their properties from being multi-element systems that can crystallize as a single phase, despite containing high concentrations of five or more elements with different crystal structures. Here we examine an equiatomic medium-entropy alloy containing only three elements, CrCoNi, as a single-phase face-centered cubic (fcc) solid solution, which displays strength-toughness properties that exceed those of all high-entropy alloys and most multi-phase alloys. At room temperature the alloy shows tensile strengths of almost 1 GPa, failure strains of ~70%, and KJIc fracture-toughness values above 200 MPa.m1/2; at cryogenic temperatures strength, ductility and toughness of the CrCoNi alloy improve to strength levels above 1.3 GPa, failure strains up to 90% and KJIc values of 275 MPa.m1/2. Such properties appear to result from continuous steady strain hardening, which acts to suppress plastic instability, resulting from pronounced dislocation activity and deformation-induced nano-twinning.Comment: 7 pages, 4 figure

Post-marketing safety surveillance for inactivated and live-attenuated Japanese encephalitis vaccines in China, 2008-2013

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.

Exploratory spatial data analysis for the identification of risk factors to birth defects

BACKGROUND: Birth defects, which are the major cause of infant mortality and a leading cause of disability, refer to "Any anomaly, functional or structural, that presents in infancy or later in life and is caused by events preceding birth, whether inherited, or acquired (ICBDMS)". However, the risk factors associated with heredity and/or environment are very difficult to filter out accurately. This study selected an area with the highest ratio of neural-tube birth defect (NTBD) occurrences worldwide to identify the scale of environmental risk factors for birth defects using exploratory spatial data analysis methods. METHODS: By birth defect registers based on hospital records and investigation in villages, the number of birth defects cases within a four-year period was acquired and classified by organ system. The neural-tube birth defect ratio was calculated according to the number of births planned for each village in the study area, as the family planning policy is strictly adhered to in China. The Bayesian modeling method was used to estimate the ratio in order to remove the dependence of variance caused by different populations in each village. A recently developed statistical spatial method for detecting hotspots, Getis's [Image: see text] [7], was used to detect the high-risk regions for neural-tube birth defects in the study area. RESULTS: After the Bayesian modeling method was used to calculate the ratio of neural-tube birth defects occurrences, Getis's [Image: see text] statistics method was used in different distance scales. Two typical clustering phenomena were present in the study area. One was related to socioeconomic activities, and the other was related to soil type distributions. CONCLUSION: The fact that there were two typical hotspot clustering phenomena provides evidence that the risk for neural-tube birth defect exists on two different scales (a socioeconomic scale at 6.84 km and a soil type scale at 22.8 km) for the area studied. Although our study has limited spatial exploratory data for the analysis of the neural-tube birth defect occurrence ratio and for finding clues to risk factors, this result provides effective clues for further physical, chemical and even more molecular laboratory testing according to these two spatial scales

Precise Measurements of Branching Fractions for Ds+D_s^+ Meson Decays to Two Pseudoscalar Mesons

We measure the branching fractions for seven $D_{s}^{+}$ two-body decays to pseudo-scalar mesons, by analyzing data collected at $\sqrt{s}=4.178\sim4.226$ GeV with the BESIII detector at the BEPCII collider. The branching fractions are determined to be $\mathcal{B}(D_s^+\to K^+\eta^{\prime})=(2.68\pm0.17\pm0.17\pm0.08)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta^{\prime}\pi^+)=(37.8\pm0.4\pm2.1\pm1.2)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\eta)=(1.62\pm0.10\pm0.03\pm0.05)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta\pi^+)=(17.41\pm0.18\pm0.27\pm0.54)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+K_S^0)=(15.02\pm0.10\pm0.27\pm0.47)\times10^{-3}$, $\mathcal{B}(D_s^+\to K_S^0\pi^+)=(1.109\pm0.034\pm0.023\pm0.035)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\pi^0)=(0.748\pm0.049\pm0.018\pm0.023)\times10^{-3}$, where the first uncertainties are statistical, the second are systematic, and the third are from external input branching fraction of the normalization mode $D_s^+\to K^+K^-\pi^+$. Precision of our measurements is significantly improved compared with that of the current world average values

Basal Immunoglobulin Signaling Actively Maintains Developmental Stage in Immature B Cells

In developing B lymphocytes, a successful V(D)J heavy chain (HC) immunoglobulin (Ig) rearrangement establishes HC allelic exclusion and signals pro-B cells to advance in development to the pre-B stage. A subsequent functional light chain (LC) rearrangement then results in the surface expression of IgM at the immature B cell stage. Here we show that interruption of basal IgM signaling in immature B cells, either by the inducible deletion of surface Ig via Cre-mediated excision or by incubating cells with the tyrosine kinase inhibitor herbimycin A or the phosphatidylinositol 3-kinase inhibitor wortmannin, led to a striking “back-differentiation” of cells to an earlier stage in B cell development, characterized by the expression of pro-B cell genes. Cells undergoing this reversal in development also showed evidence of new LC gene rearrangements, suggesting an important role for basal Ig signaling in the maintenance of LC allelic exclusion. These studies identify a previously unappreciated level of plasticity in the B cell developmental program, and have important implications for our understanding of central tolerance mechanisms

Diet supplementation for 5 weeks with polyphenol-rich cereals improves several functions and the redox state of mouse leucocytes

BACKGROUND: Cereals naturally contain a great variety of polyphenols, which exert a wide range of physiological effects both in vitro and in vivo. Many of their protective effects, including an improvement of the function and redox state of immune cells in unhealthy or aged subjects come from their properties as powerful antioxidant compounds. However, whether cereal-based dietary supplementation positively affects the immune function and cellular redox state of healthy subjects remains unclear. AIM OF THE STUDY: To investigate the effects of supplementation (20% wt/wt) for 5 weeks with four different cereal fractions on healthy mice. METHODS: Several parameters of function and redox state of peritoneal leukocytes were measured. The cereals, named B (wheat germ), C (buckwheat flour), D (fine rice bran) and E (wheat middlings) contained different amounts of gallic acid, p-hydroxybenzoic acid, vanillic acid, sinapic acid, p-coumaric acid, ferulic acid, quercetin, catechin, rutin and oryzanol as major polyphenols. RESULTS: In general, all cereal fractions caused an improvement of the leukocyte parameters studied such as chemotaxis capacity, microbicidal activity, lymphoproliferative response to mitogens, interleukin-2 (IL-2) and tumor necrosis factor (TNFα) release, as well as oxidized glutathione (GSSG), GSSG/GSH ratio, catalase (CAT) activity and lipid oxidative damage. We observed similar effects among the cereal fractions. CONCLUSIONS: The results suggest that some of these effects may due, at least partially, to the antioxidant activity of the polyphenols naturally present in cereals. Since an appropriate function of the leukocytes has been proposed as marker of the health state, a short-term intake of cereals seems to be sufficient to exert a benefit in the health of the general population. However, further studies are needed to assess the optimal doses and to find out which active polyphenols are able to mediate the observed physiological effects before recommending their regular consumption