187 research outputs found
An alternative approach to the -meson-exchange in nucleon-nucleon interaction
Through a quantitative comparative study of the properties of deuteron and
nucleon-nucleon interaction with chiral quark model and quark delocalization
color screening model. We show that the -meson exchange used in the
chiral quark model can be replaced by quark delocalization and color screening
mechanism.Comment: 4 pages, 4 figure
Leveraging TLA+ Specifications to Improve the Reliability of the ZooKeeper Coordination Service
ZooKeeper is a coordination service, widely used as a backbone of various
distributed systems. Though its reliability is of critical importance, testing
is insufficient for an industrial-strength system of the size and complexity of
ZooKeeper, and deep bugs can still be found. To this end, we resort to formal
TLA+ specifications to further improve the reliability of ZooKeeper. Our
primary objective is usability and automation, rather than full verification.
We incrementally develop three levels of specifications for ZooKeeper. We first
obtain the protocol specification, which unambiguously specifies the Zab
protocol behind ZooKeeper. We then proceed to a finer grain and obtain the
system specification, which serves as the super-doc for system development. In
order to further leverage the model-level specification to improve the
reliability of the code-level implementation, we develop the test
specification, which guides the explorative testing of the ZooKeeper
implementation. The formal specifications help eliminate the ambiguities in the
protocol design and provide comprehensive system documentation. They also help
find critical deep bugs in system implementation, which are beyond the reach of
state-of-the-art testing techniques. Our specifications have been merged into
the official Apache ZooKeeper project
Low Temperature Oxidation Experiments and Kinetics Model of Heavy Oil
Air injection is an effective technique for improved oil recovery. For a typical heavy oil sample, the effects of temperature on the oxidation characteristics were studied by low temperature oxidation (LTO) experiments. Kinetic parameters such as activation energy, frequency factor (pre-exponential factor) and reaction order are determined by using Arrhenius Equation. These parameters provide a theoretical basis for numerical simulation of LTO taking place during air injection in heavy oil reservoirs. The results of LTO experiments show that heavy oil has good low temperature oxidation properties and LTO reaction rate is mainly related to temperature, oxygen partial pressure and properties of crude oil. In the experimental temperature range, the oxidation reaction can effectively consume oxygen and at the same time produce large amount of CO2.Key words: Air injection; Low temperature oxidation; Kinetics model (70-150 oC
MXene-based Membranes for Drinking Water Production
The soaring development of industry exacerbates the shortage of fresh water, making drinking water production an urgent demand. Membrane techniques feature the merits of high efficiency, low energy consumption, and easy operation, deemed as the most potential technology to purify water. Recently, a new type of two-dimensional materials, MXenes as the transition metal carbides or nitrides in the shape of nanosheets, have attracted enormous interest in water purification due to their extraordinary properties such as adjustable hydrophilicity, easy processibility, antifouling resistance, mechanical strength, and light-to-heat transformation capability. In pioneering studies, MXene-based membranes have been evaluated in the past decade for drinking water production including the separation of bacteria, dyes, salts, and heavy metals. This review focuses on the recent advancement of MXene-based membranes for drinking water production. A brief introduction of MXenes is given first, followed by descriptions of their unique properties. Then, the preparation methods of MXene membranes are summarized. The various applications of MXene membranes in water treatment and the corresponding separation mechanisms are discussed in detail. Finally, the challenges and prospects of MXene membranes are presented with the hope to provide insightful guidance on the future design and fabrication of high-performance MXene membranes
The Photosynthetic Characteristics of \u3cem\u3eHemarthria compressa\u3c/em\u3e in Different Seasons
MiR-103a targeting Piezo1 is involved in acute myocardial infarction through regulating endothelium function
Background: Acute myocardial infarction (AMI) is commonly known as the heart attack. The molecular events involved in the development of AMI remain unclear. This study was to investigate the expression of miR-103a in patients with high blood pressure (HBP) and AMI patients with and without HBP, as well as its effect on endothelial cell functions.
Methods: MiR-103a expression in plasma and peripheral blood mononuclear cells (PBMCs) was measured by real-time polymerase chain reaction (PCR). The regulatory effect of miR-103a on Piezo1 gene was identified by a luciferase reporter system. The role of miR-103a in endothelial cells was evaluated by the capillary tube formation ability and cell viability of human umbilical vein endothelial cells (HUVECs).
Results: The plasma miR-103a concentration was significantly elevated in patients with HBP alone, AMI alone, and comorbidity of AMI and HBP. The miR-103a expression in PBMCs in patients with AMI and HBP was significantly higher than the one in healthy controls (p < 0.05), however miR-103a expression in PBMCs was not significantly different among patients with HBP alone, patients with AMI alone, and healthy controls. MiR-103a targeted Piezo1 and inhibited Piezo1 protein expression, which subsequently reduced capillary tube formation ability and cell viability of HUVECs.
Conclusions: MiR-103a might be a potential biomarker of myocardium infarction and could be used as an index for the diagnosis of AMI. It may be involved in the development of HBP and onset of AMI through regulating the Piezo1 expression.
Finetuning Large-Scale Pre-trained Language Models for Conversational Recommendation with Knowledge Graph
In this paper, we present a pre-trained language model (PLM) based framework
called RID for conversational recommender system (CRS). RID finetunes the
large-scale PLMs such as DialoGPT, together with a pre-trained Relational Graph
Convolutional Network (RGCN) to encode the node representations of an
item-oriented knowledge graph. The former aims to generate fluent and diverse
dialogue responses based on the strong language generation ability of PLMs,
while the latter is to facilitate the item recommendation by learning better
node embeddings on the structural knowledge base. To unify two modules of
dialogue generation and item recommendation into a PLMs-based framework, we
expand the generation vocabulary of PLMs to include an extra item vocabulary,
and introduces a vocabulary pointer to control when to recommend target items
in the generation process. Extensive experiments on the benchmark dataset
ReDial show RID significantly outperforms the state-of-the-art methods on both
evaluations of dialogue and recommendation
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