614 research outputs found
Alcohol on drinking experience and attitudes towards sexual behaviors among female students in a Guangzhou technical secondary school
published_or_final_versio
Exploring the "energy-saving personality traits" in the office and household situation: An empirical study
Behavior-driven energy conservation has been a promising strategy for reducing building energy consumption as well as carbon emissions. With the intention of revealing the impacts of an individual’s personality basis on energy conservation behavioral attitudes and intentions in households and offices, the present study proposes and conducts an experiment in Xi’an, China with two groups for the investigation of such attitudes towards household energy-saving behavior (HESB) and office energy-saving behavior (OESB), respectively. The research adopts structural equation modeling for experiment data analysis. The analysis results suggest that the two personality traits, Agreeableness and Neuroticism, are significantly related to both HESB and OESB attitudes. Especially, agreeable people tend to present stronger energy-saving attitudes, while individuals with higher Neuroticism are less likely to do so. The results indicate that the impacts of these two traits on energy-saving attitude are found to be less influenced by different environment settings. Further, the results find that Extraversion positively influences energy-saving attitude in the office environment, while Openness only significantly works in the household environment. It is hoped that the findings of the present study can provide informative references to energy-saving intervention design as well as further studies on the spillover of pro-environmental behaviors.</jats:p
A Substrate Scheduler for Compiling Arbitrary Fault-tolerant Graph States
Graph states are useful computational resources in quantum computing,
particularly in measurement-based quantum computing models. However, compiling
arbitrary graph states into executable form for fault-tolerant surface code
execution and accurately estimating the compilation cost and the run-time
resource cost remains an open problem. We introduce the Substrate Scheduler, a
compiler module designed for fault-tolerant graph state compilation. The
Substrate Scheduler aims to minimize the space-time volume cost of generating
graph states. We show that Substrate Scheduler can efficiently compile graph
states with thousands of vertices for "A Game of Surface Codes"-style
patch-based surface code systems. Our results show that our module generates
graph states with the lowest execution time complexity to date, achieving graph
state generation time complexity that is at or below linear in the number of
vertices and demonstrating specific types of graphs to have constant generation
time complexity. Moreover, it provides a solid foundation for developing
compilers that can handle a larger number of vertices, up to the millions or
billions needed to accommodate a wide range of post-classical quantum computing
applications.Comment: 11 pages, 11 figure
Superderivations for Modular Graded Lie Superalgebras of Cartan-type
Superderivations for the eight families of finite or infinite dimensional
graded Lie superalgebras of Cartan-type over a field of characteristic
are completely determined by a uniform approach: The infinite dimensional case
is reduced to the finite dimensional case and the latter is further reduced to
the restrictedness case, which proves to be far more manageable. In particular,
the outer superderivation algebras of those Lie superalgebras are completely
determined
Psychological drivers of hotel guests’ energy‐saving behaviours—empirical research based on the extended theory of planned behaviour
The hospitality industry is an important energy consumer and carbon emitter. Behaviour-driven energy conservation is a strategy with great promise to strengthen the energy efficiency of hotel buildings. The aim of this study is to explore the driving psychological factors of hotel guests’ energy-saving intentions and behaviours. This paper constructs two extensions of the theory of planned behaviour (TPB) with personal norms, past behaviours, and self-determined motivation to explain the guests’ energy-saving behaviour in hotel buildings. This research compares the explanatory power of the original TPB and two extensions with structural equation modelling. The analysis is based on 530 valid, self-reported data from 827 surveyed hotel guests in Shanghai. The analysis suggests that the extended model gains greater explanatory power in predicting the behaviour patterns by employing the above three additional factors. In addition, self-determined motivation presents a more significant impact than other more developed TPB predictors, such as intention and perceived behaviour control. Aside from that, past behaviour replaces attitude as the most critical predictor of hotel energy-saving intention in the extended models. In addition to the existing interventions in office and residential buildings, the research highlights the role of self-determination in hotel energy conservation and further emphasises the long-term benefit of encouraging pro-environmental behaviours in hotel guests. The findings expand the existing research on pro-environmental behaviours and will contribute to energy-saving behaviour intervention in hotel buildings and policy formulations for sustainable hotel operation and maintenance.</jats:p
Recovery from Mercury Contamination in the Second Songhua River, China
Mercury pollution in the Second Songhua River (SSR) was serious in the last century due to effluent from a chemical corporation. Effects of riverine self-purification on mercury removal were studied by comparing monitoring data of mercury concentrations varieties in water, sediment, and fish in the past, about 30 years. The present work suggested that a river of such a size like the SSR possessed the potential ability to recover from mercury pollution under the condition that mercury sources were cut off, though it needs a very long time, which might be several decades or even a century of years. During the 30 years with no effluent containing mercury input, total mercury (T-Hg) of water and sediment in some typical segments, mostly near the past effluent outlet, had decreased radically but still higher than the background values, though the decrease amplitudes were over 90% compared with that in 1975. T-Hg had decreased by more than 90% in most fishes, but some were still not suitable for consumption. Methylmercury concentrations (MeHg) of water, sediment, and fish were higher or close to the background levels in 2004. In the coming decades, the purification processes in the SSR would be steady and slow for a long period
In situ epitaxial engineering of graphene and h-BN lateral heterostructure with a tunable morphology comprising h-BN domains
Graphene and hexagonal boron nitride (h-BN), as typical two-dimensional (2D) materials, have long attracted substantial attention due to their unique properties and promise in a wide range of applications. Although they have a rather large difference in their intrinsic bandgaps, they share a very similar atomic lattice; thus, there is great potential in constructing heterostructures by lateral stitching. Herein, we present the in situ growth of graphene and h-BN lateral heterostructures with tunable morphologies that range from a regular hexagon to highly symmetrical star-like structure on the surface of liquid Cu. The chemical vapor deposition (CVD) method is used, where the growth of the h-BN is demonstrated to be highly templated by the graphene. Furthermore, large-area production of lateral G-h-BN heterostructures at the centimeter scale with uniform orientation is realized by precisely tuning the CVD conditions. We found that the growth of h-BN is determined by the initial graphene and symmetrical features are produced that demonstrate heteroepitaxy. Simulations based on the phase field and density functional theories are carried out to elucidate the growth processes of G-h-BN flakes with various morphologies, and they have a striking consistency with experimental observations. The growth of a lateral G-h-BN heterostructure and an understanding of the growth mechanism can accelerate the construction of various heterostructures based on 2D materials
Microstructure and dry sliding wear behavior of cast Al–Mg2Si in-situ metal matrix composite modified by Nd
Downgrading MELD Improves the Outcomes after Liver Transplantation in Patients with Acute-on-Chronic Hepatitis B Liver Failure
Background: High score of model for end-stage liver diseases (MELD) before liver transplantation (LT) indicates poor prognosis. Artificial liver support system (ALSS) has been proved to effectively improve liver and kidney functions, and thus reduce the MELD score. We aim to evaluate whether downgrading MELD score could improve patient survival after LT. Methodology/Principal Findings: One hundred and twenty-six LT candidates with acute-on-chronic hepatitis B liver failure and MELD score 30 was effective i
Predicting protein-protein interface residues using local surface structural similarity
<p>Abstract</p> <p>Background</p> <p>Identification of the residues in protein-protein interaction sites has a significant impact in problems such as drug discovery. Motivated by the observation that the set of interface residues of a protein tend to be conserved even among remote structural homologs, we introduce <it>PrISE</it>, a family of local structural similarity-based computational methods for predicting protein-protein interface residues.</p> <p>Results</p> <p>We present a novel representation of the surface residues of a protein in the form of structural elements. Each structural element consists of a central residue and its surface neighbors. The <it>PrISE </it>family of interface prediction methods uses a representation of structural elements that captures the atomic composition and accessible surface area of the residues that make up each structural element. Each of the members of the <it>PrISE </it>methods identifies for each structural element in the query protein, a collection of <it>similar </it>structural elements in its repository of structural elements and weights them according to their similarity with the structural element of the query protein. <it>PrISE<sub>L </sub></it>relies on the similarity between structural elements (i.e. local structural similarity). <it>PrISE<sub>G </sub></it>relies on the similarity between protein surfaces (i.e. general structural similarity). <it>PrISE<sub>C</sub></it>, combines local structural similarity and general structural similarity to predict interface residues. These predictors label the central residue of a structural element in a query protein as an interface residue if a weighted majority of the structural elements that are similar to it are interface residues, and as a non-interface residue otherwise. The results of our experiments using three representative benchmark datasets show that the <it>PrISE<sub>C </sub></it>outperforms <it>PrISE<sub>L </sub></it>and <it>PrISE<sub>G</sub></it>; and that <it>PrISE<sub>C </sub></it>is highly competitive with state-of-the-art structure-based methods for predicting protein-protein interface residues. Our comparison of <it>PrISE<sub>C </sub></it>with <it>PredUs</it>, a recently developed method for predicting interface residues of a query protein based on the known interface residues of its (global) structural homologs, shows that performance superior or comparable to that of <it>PredUs </it>can be obtained using only local surface structural similarity. <it>PrISE<sub>C </sub></it>is available as a Web server at <url>http://prise.cs.iastate.edu/</url></p> <p>Conclusions</p> <p>Local surface structural similarity based methods offer a simple, efficient, and effective approach to predict protein-protein interface residues.</p
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