291 research outputs found
Characterising User Transfer Amid Industrial Resource Variation: A Bayesian Nonparametric Approach
In a multitude of industrial fields, a key objective entails optimising
resource management whilst satisfying user requirements. Resource management by
industrial practitioners can result in a passive transfer of user loads across
resource providers, a phenomenon whose accurate characterisation is both
challenging and crucial. This research reveals the existence of user clusters,
which capture macro-level user transfer patterns amid resource variation. We
then propose CLUSTER, an interpretable hierarchical Bayesian nonparametric
model capable of automating cluster identification, and thereby predicting user
transfer in response to resource variation. Furthermore, CLUSTER facilitates
uncertainty quantification for further reliable decision-making. Our method
enables privacy protection by functioning independently of personally
identifiable information. Experiments with simulated and real-world data from
the communications industry reveal a pronounced alignment between prediction
results and empirical observations across a spectrum of resource management
scenarios. This research establishes a solid groundwork for advancing resource
management strategy development
A Semi-supervised Graph Attentive Network for Financial Fraud Detection
With the rapid growth of financial services, fraud detection has been a very
important problem to guarantee a healthy environment for both users and
providers. Conventional solutions for fraud detection mainly use some
rule-based methods or distract some features manually to perform prediction.
However, in financial services, users have rich interactions and they
themselves always show multifaceted information. These data form a large
multiview network, which is not fully exploited by conventional methods.
Additionally, among the network, only very few of the users are labelled, which
also poses a great challenge for only utilizing labeled data to achieve a
satisfied performance on fraud detection.
To address the problem, we expand the labeled data through their social
relations to get the unlabeled data and propose a semi-supervised attentive
graph neural network, namedSemiGNN to utilize the multi-view labeled and
unlabeled data for fraud detection. Moreover, we propose a hierarchical
attention mechanism to better correlate different neighbors and different
views. Simultaneously, the attention mechanism can make the model interpretable
and tell what are the important factors for the fraud and why the users are
predicted as fraud. Experimentally, we conduct the prediction task on the users
of Alipay, one of the largest third-party online and offline cashless payment
platform serving more than 4 hundreds of million users in China. By utilizing
the social relations and the user attributes, our method can achieve a better
accuracy compared with the state-of-the-art methods on two tasks. Moreover, the
interpretable results also give interesting intuitions regarding the tasks.Comment: icd
Unequal Perylene Diimide Twins in a Quadruple Assembly
Natural light-harvesting (LH) systems can divide identical dyes into unequal aggregate states, thereby achieving intelligent "allocation of labor". From a synthetic point of view, the construction of such kinds of unequal and integrated systems without the help of proteinaceous scaffolding is challenging. Here, we show that four octatetrayne-bridged ortho-perylene diimide (PDI) dyads (POPs) self-assemble into a quadruple assembly (POP)4 both in solution and in the solid state. The two identical PDI units in each POP are compartmentalized into weakly coupled PDIs (P520) and closely stacked PDIs (P550) in (POP)4 . The two extreme pools of PDI chromophores were unambiguously confirmed by single-crystal X-ray crystallography and NMR spectroscopy. To interpret the formation of the discrete quadruple assembly, we also developed a two-step cooperative model. Quantum-chemical calculations indicate the existence of multiple couplings within and across P520 and P550, which can satisfactorily describe the photophysical properties of the unequal quadruple assembly. This finding is expected to help advance the rational design of dye stacks to emulate functions of natural LH systems.</p
Perioperative probiotics attenuates postoperative cognitive dysfunction in elderly patients undergoing hip or knee arthroplasty: A randomized, double-blind, and placebo-controlled trial
BackgroundPostoperative cognitive dysfunction (POCD) is a common complication in elderly patients following surgery. The preventive and/or treatment strategies for the incidence remain limited.ObjectiveThis study aimed to investigate the preventive effect of perioperative probiotic treatment on POCD in elderly patients undergoing hip or knee arthroplasty.MethodsAfter obtaining ethical approval and written informed consent, 106 patients (age ≥60 years) were recruited, who scheduled elective hip or knee arthroplasty, from 16 March 2021 to 25 February 2022 for this randomized, double-blind, and placebo-controlled trial. They were randomly assigned with a 1:1 ratio to receive either probiotics or placebo treatment (four capsules, twice/day) from hospital admission until discharge. Cognitive function was assessed with a battery of 11 neuropsychological tests on the admission day and the seventh day after surgery, respectively.ResultsA total of 96 of 106 patients completed the study, and their data were finally analyzed. POCD occurred in 12 (26.7%) of 45 patients in the probiotic group and 29 (56.9%) of 51 patients in the placebo group (relative risk [RR], 0.47 [95% confidence interval [CI], 0.27 to 0.81]; P = 0.003). Among them, mild POCD occurred in 11 (24.4%) in the probiotic group and 24 (47.1%) in the placebo group (RR, 0.52 [95% CI, 0.29 to 0.94]; P = 0.022). No significant difference in severe POCD incidence was found between the two groups (P = 0.209). Compared with the placebo group, the verbal memory domain cognitive function was mainly improved in the probiotic group.ConclusionProbiotics may be used perioperatively to prevent POCD development and improve verbal memory performance in elderly patients receiving hip or knee arthroplasty.Clinical trial registrationwww.chictr.org.cn, identifier: ChiCTR2100045620
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