Magic ratios for connectivity-driven electrical conductance of graphene-like molecules

Experiments using a mechanically-controlled break junction and calculations based on density functional theory demonstrate a new magic ratio rule (MRR),which captures the contribution of connectivity to the electrical conductance of graphene-like aromatic molecules. When one electrode is connected to a site i and the other is connected to a site i' of a particular molecule, we assign the molecule a magic integer Mii'. Two molecules with the same aromatic core, but different pairs of electrode connection sites (i,i' and j,j' respectively) possess different magic integers Mii' and Mjj'. Based on connectivity alone, we predict that when the coupling to electrodes is weak and the Fermi energy of the electrodes lies close to the centre of the HOMO-LUMO gap, the ratio of their conductances is equal to (Mii' /Mjj')2. The MRR is exact for a tight binding representation of a molecule and a qualitative guide for real molecules

Astragalus Polysaccharides Lowers Plasma Cholesterol through Mechanisms Distinct from Statins

To determine the efficacy and underlying mechanism of Astragalus polysaccharides (APS) on plasma lipids in hypercholesterolemia hamsters. The effect of APS (0.25g/kg/d) on plasma and liver lipids, fecal bile acids and neutral sterol, cholesterol absorption and synthesis, HMG-CoA reductase activity, and gene and protein expressions in the liver and small intestine was investigated in twenty-four hypercholesterolemia hamsters. Treatment periods lasted for three months. APS significantly lowered plasma total cholesterol by 45.8%, triglycerides by 30%, and low-density lipoprotein-cholesterol by 47.4%, comparable to simvastatin. Further examinations revealed that APS reduced total cholesterol and triglycerides in the liver, increased fecal bile acid and neutral sterol excretion, inhibited cholesterol absorption, and by contrast, increased hepatic cholesterol synthesis and HMG-CoA reductase activity. Plasma total cholesterol or low-density lipoprotein-cholesterol levels were significantly correlated with cholesterol absorption rates. APS up-regulated cholesterol-7α-hydroxylase and LDL-receptor gene expressions. These new findings identify APS as a potential natural cholesterol lowering agent, working through mechanisms distinct from statins

Factors related to the quality of life of family cancer caregivers

BackgroundCancer caregivers directly affect patient health outcomes. To maintain the function and health of caregivers so that patients can receive efficient care, we must pay more attention to caregivers’ quality of life in the process of caring for patients. However, the factors influencing caregivers’ quality of life are complex.AimTo assess caregivers’ quality of life in the process of caring for cancer patients and to explore the factors associated with it.DesignThis was a descriptive correlational study. A self-report questionnaire was used to anonymously collect data from one Chinese cancer hospital. The Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being (FACIT-Sp-12), General Self-efficacy Scale (GSES), Positive and Negative Affect Schedule (PANAS), Connor-Davidson Resilience Scale 10 (CD-RISC-10), 24-item Caregiver Burden Inventory (CBI) and Caregiver Evaluation Questionnaire were used to measure caregivers’ spiritual well-being, self-efficacy, affective well-being, resilience, caregiver burden and quality of life. One-way analysis of variance, the Kruskal–Wallis H test and multiple regression analysis were applied to measure the factors influencing caregivers’ situations.Setting and participantsA total of 315 caregivers of cancer patients were selected by convenience sampling. All participants were invited to complete the questionnaire through a one-on-one approach.ResultsThe mean score for caregiver quality of life was 204.62 ± 36.61. After controlling for demographic factors, self-efficacy (β’ = 0.265, p < 0.01), resilience (β’ = 0.287, p < 0.01) and positive affect (β’ = 0.103, p < 0.01) were protective factors for caregivers’ quality of life. Negative affect (β’ = −0.217, p < 0.01) and caregiver burden (β’ = −0.219, p < 0.01) were negative factors. Notably, not all of these predictors can predict all dimensions of quality of life.ConclusionCaregivers’ quality of life needs to be further improved. The results of this study may provide clues to help identify factors influencing caregivers’ quality of life and implement targeted strategies to improve their quality of life

The spontaneous escape behavior of silver from graphite-like carbon coatings and its effect on corrosion resistance

Silver-doped graphite-like carbon (Ag-GLC) coatings were prepared on the surface of aluminum alloy and single-crystal silicon by magnetron sputtering under different deposition parameters. The effects of silver target current and deposition temperature, as well as of the addition of CH4 gas flow, on the spontaneous escape behavior of silver from the GLC coatings were investigated. Furthermore, the corrosion resistance of the Ag-GLC coatings were evaluated. The results showed that the spontaneous escape phenomenon of silver could take place at the GLC coating, regardless of preparation condition. These three preparation factors all had an influence on the size, number and distribution of the escaped silver particles. However, in contrast with the silver target current and the addition of CH4 gas flow, only the change in deposition temperature had a significant positive effect on the corrosion resistance of the Ag-GLC coatings. The Ag-GLC coating showed the best corrosion resistance when the deposition temperature was 500 °C, which was due to the fact that increasing the deposition temperature effectively reduced the number of silver particles escaping from the Ag-GLC coating

Hard Sample Aware Network for Contrastive Deep Graph Clustering

Contrastive deep graph clustering, which aims to divide nodes into disjoint groups via contrastive mechanisms, is a challenging research spot. Among the recent works, hard sample mining-based algorithms have achieved great attention for their promising performance. However, we find that the existing hard sample mining methods have two problems as follows. 1) In the hardness measurement, the important structural information is overlooked for similarity calculation, degrading the representativeness of the selected hard negative samples. 2) Previous works merely focus on the hard negative sample pairs while neglecting the hard positive sample pairs. Nevertheless, samples within the same cluster but with low similarity should also be carefully learned. To solve the problems, we propose a novel contrastive deep graph clustering method dubbed Hard Sample Aware Network (HSAN) by introducing a comprehensive similarity measure criterion and a general dynamic sample weighing strategy. Concretely, in our algorithm, the similarities between samples are calculated by considering both the attribute embeddings and the structure embeddings, better revealing sample relationships and assisting hardness measurement. Moreover, under the guidance of the carefully collected high-confidence clustering information, our proposed weight modulating function will first recognize the positive and negative samples and then dynamically up-weight the hard sample pairs while down-weighting the easy ones. In this way, our method can mine not only the hard negative samples but also the hard positive sample, thus improving the discriminative capability of the samples further. Extensive experiments and analyses demonstrate the superiority and effectiveness of our proposed method.Comment: 9 pages, 6 figure

The relationship between resilience and quality of life in advanced cancer survivors: multiple mediating effects of social support and spirituality

BackgroundWhile previous studies have revealed a positive association between resilience and quality of life in advanced cancer survivors, the mechanisms of the relationship is still unclear. This study aimed to explore the relationships between resilience, social support, spirituality, and quality of life and determine the multiple mediation effects of social support and spirituality on the relationship between resilience and quality of life.MethodsWith 286 advanced cancer survivors, a cross-sectional, correlational survey was adopted using convenience sampling. Resilience, social support, spirituality, and quality of life were evaluated by self-report questionnaires. The PROCESS macro for SPSS was used to test the multiple mediation model.ResultsThe scores for resilience, social support, spirituality and quality of life were positively correlated with one another. Resilience was found to be directly impact quality of life. Meanwhile, the relationship between resilience and quality of life was mediated by social support (effect = 0.067, 95% CI [0.019, 0.120]) and by spirituality (effect = 0.221, 95% CI [0.134, 0.332]), respectively, and by these two serially (effect = 0.036, 95% CI [0.015, 0.067]).ConclusionSocial support and spirituality played multiple mediating roles in the relationship between resilience and quality of life. Interventions aimed at increasing resilience, and then boosting social support and spirituality may be beneficial for promoting quality of life of advanced cancer survivors

Searching the hearts of graphene-like molecules for simplicity, sensitivity and logic

If quantum interference patterns in the hearts of polycyclic aromatic hydrocarbons (PAHs) could be isolated and manipulated, then a significant step towards realizing the potential of single-molecule electronics would be achieved. Here we demonstrate experimentally and theoretically that a simple, parameter-free, analytic theory of interference patterns evaluated at the mid-point of the HOMO-LUMO gap (referred to as M-functions) correctly predicts conductance ratios of molecules with pyrene, naphthalene, anthracene, anthanthrene or azulene hearts. M-functions provide new design strategies for identifying molecules with phase-coherent logic functions and enhancing the sensitivity of molecular-scale interferometers.Comment: in J. Am. Chem. Soc. (2015

Divergent taxonomic and functional responses of microbial communities to field simulation of aeolian soil erosion and deposition.

Aeolian soil erosion and deposition have worldwide impacts on agriculture, air quality and public health. However, ecosystem responses to soil erosion and deposition remain largely unclear in regard to microorganisms, which are the crucial drivers of biogeochemical cycles. Using integrated metagenomics technologies, we analysed microbial communities subjected to simulated soil erosion and deposition in a semiarid grassland of Inner Mongolia, China. As expected, soil total organic carbon and plant coverage were decreased by soil erosion, and soil dissolved organic carbon (DOC) was increased by soil deposition, demonstrating that field simulation was reliable. Soil microbial communities were altered (p < .039) by both soil erosion and deposition, with dramatic increase in Cyanobacteria related to increased stability in soil aggregates. amyA genes encoding α-amylases were specifically increased (p = .01) by soil deposition and positively correlated (p = .02) to DOC, which likely explained changes in DOC. Surprisingly, most of microbial functional genes associated with carbon, nitrogen, phosphorus and potassium cycling were decreased or unaltered by both erosion and deposition, probably arising from acceleration of organic matter mineralization. These divergent responses support the necessity to include microbial components in evaluating ecological consequences. Furthermore, Mantel tests showed strong, significant correlations between soil nutrients and functional structure but not taxonomic structure, demonstrating close relevance of microbial function traits to nutrient cycling

Predicting global potential distribution of Peromyscopsylla hesperomys and Orchopeas sexdentatus and risk assessment for invading China under climate change

BackgroundPeromyscopsylla hesperomys and Orchopeas sexdentatus are regarded to be representative plague vectors in the United States. The incidence of plague is rising globally, possibly due to climate change and environmental damage. Environmental factors such as temperature and precipitation have a significant impact on the temporal and spatial distribution of plague vectors.MethodsMaximum entropy models (MaxEnt) were utilized to predict the distributions of these two fleas and their trends into the future. The main environmental factors influencing the distribution of these two fleas were analyzed. A risk assessment system was constructed to calculate the invasion risk values of the species.ResultsTemperature has a significant effect on the distribution of the potentially suitable areas for P. hesperomys and O. sexdentatus. They have the potential to survive in suitable areas of China in the future. The risk assessment system indicated that the risk level for the invasion of these two species into China was moderate.ConclusionIn order to achieve early detection, early interception, and early management, China should perfect its monitoring infrastructure and develop scientific prevention and control strategies to prevent the invasion of foreign flea vectors