Publications by authors named "Xuefeng Dai"

Objectives: To investigate the effects of different angles of pulmonary surfactant (PS) administration on the incidence of bronchopulmonary dysplasia and intracranial hemorrhage in preterm infants.

Methods: A prospective study was conducted on 146 preterm infants (gestational age <32 weeks) admitted to the Department of Neonatology, Provincial Hospital Affiliated to Anhui Medical University from January 2019 to May 2023. The infants were randomly assigned to different angles for injection of pulmonary surfactant groups: 0° group (34 cases), 30° group (36 cases), 45° group (38 cases), and 60° group (38 cases).

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Indoor positioning is the basic requirement of future positioning services, and high-precision, low-cost indoor positioning algorithms are the key technology to achieve this goal. Different from outdoor maps, indoor data has the characteristic of uneven distribution and close correlation. In areas with low data density, in order to achieve a high-precision positioning effect, the positioning time will be correspondingly longer, but this is not necessary.

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We investigate the effect of quantum interference on the Andreev reflections (ARs) induced by Majorana bound states (MBSs), by considering their additional coupling via a quantum-dot molecule. It is found that due to the direct and indirect couplings of MBSs, a quantum ring is constructed in this system. Consequently, the interference effect makes important contribution to the ARs, especially in the presence of the local magnetic flux.

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Background: In combination with gene expression profiles, the protein interaction network (PIN) constructs a dynamic network that includes multiple functional modules. Previous studies have demonstrated that rifampin can influence drug metabolism by regulating drug-metabolizing enzymes, transporters, and microRNAs (miRNAs). Rifampin induces gene expression, at least in part, by activating the pregnane X receptor (PXR), which induces gene expression; however, the impact of rifampin on global gene regulation has not been examined under the molecular network frameworks.

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Background: MicroRNAs (miRNAs) are short noncoding RNAs integral for regulating gene expression at the posttranscriptional level. However, experimental methods often fall short in finding miRNAs expressed at low levels or in specific tissues. While several computational methods have been developed for predicting the localization of mature miRNAs within the precursor transcript, the prediction accuracy requires significant improvement.

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The compositions and structures of thermodynamically stable or metastable precipitations in binary Mg-X (X=Sn, Y, Sc, Ag) alloys are predicted using ab-initio evolutionary algorithm. The geometry optimizations of the predicted intermetallic compounds are carried out in the framework of density functional theory (DFT) [1]. A complete list of the optimized crystallographic information (in cif format) of the predicted intermetallic phases is presented here.

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Two new ternary compounds in the TiO2-TiC system, Ti5C2O6 and Ti3C2O2, are reported for the first time based on ab initio evolutionary algorithm. Ti5C2O6 has a tube-structure in which sp(1) hybridized carbon chains run through the lattice along the b-axis; while in the Ti3C2O2 lattice, double TiO6 polyhedral are separated by the non-coplanar sp(2) hybridized hexagon graphite layers along the c-axis, forming a sandwich-like structure. At ambient conditions, the two compounds are found to be mechanically and dynamically stable and intrinsic transparent conductors with high hardness (about twice harder than the conventional transparent conducting oxides).

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Compared with noisy chaotic neural networks (NCNNs), hysteretic noisy chaotic neural networks (HNCNNs) are more likely to exhibit better optimization performance at higher noise levels, but behave worse at lower noise levels. In order to improve the optimization performance of HNCNNs, this paper presents a novel noise-tuning-based hysteretic noisy chaotic neural network (NHNCNN). Using a noise tuning factor to modulate the level of stochastic noises, the proposed NHNCNN not only balances stochastic wandering and chaotic searching, but also exhibits stronger hysteretic dynamics, thereby improving the optimization performance at both lower and higher noise levels.

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Noisy chaotic neural network (NCNN), which can exhibit stochastic chaotic simulated annealing (SCSA), has been proven to be a powerful tool in solving combinatorial optimization problems. In order to retain the excellent optimization property of SCSA and improve the optimization performance of the NCNN using hysteretic dynamics without increasing network parameters, we first construct an equivalent model of the NCNN and then control noises in the equivalent model to propose a novel hysteretic noisy chaotic neural network (HNCNN). Compared with the NCNN, the proposed HNCNN can exhibit both SCSA and hysteretic dynamics without introducing extra system parameters, and can increase the effective convergence toward optimal or near-optimal solutions at higher noise levels.

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Objective: To explore the changes of liver regeneration after partial hepatectomy on rats with nonalcoholic fatty liver disease (NAFLD) caused by a high fat diet.

Methods: One hundred Wistar rats were randomly divided into a control group (group C, n = 45), fed with normal diet, and a NAFLD group, fed with fat-rich diet (group F, n = 55). All rats had a 70% partial hepatectomy at the end of the 12th week.

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