How does Doctors’ Information Sharing Behavior Influence Reputation in Online Health Consultation Platform?

The online health consultation platforms provide a unique context for doctors to share health information privately and publicly. However, how doctors’ reputation is shaped in the context of online information sharing has been largely neglected in the current literature. This study explores the relationship between information sharing and reputation by distinguishing private and public information sharing behaviours and investigating the contingent roles of doctors’ professional and online seniority. Data from a leading online consultation platform in China was obtained to test the research model and associated hypotheses. The results reveal that both private and public sharing can contribute to doctors’ online reputation and the effects of the two information sharing behaviours are different about doctors within different professional and online seniority. This study contributes to the literature on health information sharing and online reputation development

Multi-fault classification of rotor systems based on phase feature of axis trajectory in noisy environments

As it is difficult to distinguish multiple rotor faults with similar dynamic phenomena in noisy environments, a multi-fault classification method is proposed by combining the extracted trajectory phase feature, a parameter-optimized variational mode decomposition (VMD) method and a light gradient boosting machine (LightGBM) model. The trajectory phase feature is extracted from an axis trajectory by fusing the frequency, amplitude, and phase information related to rotor motion and can comprehensively describe the dynamic characteristics induced by different rotor faults. First, the vibration displacement signals in two orthogonal directions are collected to construct the axis trajectories with 12 rotor states including healthy, unbalance, misalignment, single crack, multiple cracks, and a mixture of them. Second, the trajectory phase feature is extracted from the vectorized axis trajectories, and the frequency spectra of trajectory phase angles under different rotor faults are analyzed through Fourier transform. Finally, a parameter-optimized VMD method combined with a LightGBM model is applied to classify multiple faults of rotor systems in different noisy environments based on the extracted trajectory phase feature. The 12 rotor states can be classified into nine categories based on the harmonic information of 1X–7X components (X is the rotating frequency of a rotor system) and other components with smaller amplitudes in the frequency spectra of trajectory phase angles. The average classification accuracy of the 12 rotor states exceeds 93.0%, and the recognition rate for each kind of fault is greater than 77.5% in noisy environments. The simulated and experimental results demonstrate the effectiveness and adaptability of the proposed multi-fault classification method. This work can provide a reference for the condition monitoring and fault diagnosis of rotor systems in engineering. </jats:p

Experimental observation of Berry phases in optical Möbius-strip microcavities

The Möbius strip, a fascinating loop structure with one-sided topology, provides a rich playground for manipulating the non-trivial topological behaviour of spinning particles, such as electrons, polaritons and photons, in both real and parameter spaces. For photons resonating in a Möbius-strip cavity, the occurrence of an extra phase—known as the Berry phase—with purely topological origin is expected due to its non-trivial evolution in parameter space. However, despite numerous theoretical investigations, characterizing the optical Berry phase in a Möbius-strip cavity has remained elusive. Here we report the experimental observation of the Berry phase generated in optical Möbius-strip microcavities. In contrast to theoretical predictions in optical, electronic and magnetic Möbius-topology systems where only Berry phase π occurs, we demonstrate that a variable Berry phase smaller than π can be acquired by generating elliptical polarization of resonating light. Möbius-strip microcavities as integrable and Berry-phase-programmable optical systems are of great interest in topological physics and emerging classical or quantum photonic applications

Symmetry‐Induced Selective Excitation of Topological States in Su–Schrieffer–Heeger Waveguide Arrays

The investigation of topological state transition in carefully designed photonic lattices is of high interest for fundamental research, as well as for applied studies such as manipulating light flow in on-chip photonic systems. Herein, the topological phase transition between symmetric topological zero modes (TZM) and antisymmetric TZMs in Su–Schrieffer–Heeger mirror symmetric waveguides is reported. The transition of TZMs is realized by adjusting the coupling ratio between neighboring waveguide pairs, which is enabled by selective modulation of the refractive index in the waveguide gaps. Bidirectional topological transitions between symmetric and antisymmetric TZMs can be achieved with proposed switching strategy. Selective excitation of topological edge mode is demonstrated owing to the symmetry characteristics of the TZMs. The flexible manipulation of topological states is promising for on-chip light flow control and may spark further investigations on symmetric/antisymmetric TZM transitions in other photonic topological frameworks

Symmetry induced selective excitation of topological states in SSH waveguide arrays

The investigation of topological state transition in carefully designed photonic lattices is of high interest for fundamental research, as well as for applied studies such as manipulating light flow in on-chip photonic systems. Here, we report on topological phase transition between symmetric topological zero modes (TZM) and antisymmetric TZMs in Su-Schrieffer-Heeger (SSH) mirror symmetric waveguides. The transition of TZMs is realized by adjusting the coupling ratio between neighboring waveguide pairs, which is enabled by selective modulation of the refractive index in the waveguide gaps. Bi-directional topological transitions between symmetric and antisymmetric TZMs can be achieved with our proposed switching strategy. Selective excitation of topological edge mode is demonstrated owing to the symmetry characteristics of the TZMs. The flexible manipulation of topological states is promising for on-chip light flow control and may spark further investigations on symmetric/antisymmetric TZM transitions in other photonic topological frameworks

Macleaya cordata isoquinoline alkaloids attenuate Escherichia coli lipopolysaccharide-induced intestinal epithelium injury in broiler chickens by co-regulating the TLR4/MyD88/NF-κB and Nrf2 signaling pathways

This study sought to explore the effects and potential mechanisms of dietary supplementation with isoquinoline alkaloids (IA) from Macleaya cordata to alleviate lipopolysaccharide (LPS)-induced intestinal epithelium injury in broilers. A total of 486 1-day-old broilers were assigned at random to a control (CON) group, LPS group, and LPS+IA group in a 21-d study. The CON and LPS groups received a basal diet, while the LPS+IA group received a basal diet supplemented with 0.6 mg/kg IA. At 17, 19, and 21 days of age, the LPS and LPS+BP groups were injected intraperitoneally with LPS, and the CON group was intraperitoneally injected equivalent amount of saline solution. The results manifested that LPS injection caused intestinal inflammation and lipid peroxidation, disrupted intestinal barrier and function, and increased the abundance of harmful microorganisms. However, dietary IA supplementation alleviated LPS-induced adverse changes in intestinal morphology, apoptosis, mucosal barrier integrity, cecum microorganisms, and homeostasis disorder by decreasing inflammatory cytokines and enhancing antioxidant-related genes expressions; inhibited LPS-induced increases in TLR4 and NF-κB expressions and decreases in Nrf2 and GPX1 genes expressions. Our findings indicated that Macleaya cordata IA addition attenuated LPS-induced intestinal epithelium injury and disorder of intestinal homeostasis by enhancing the anti-inflammatory and antioxidant capacity of broiler chickens possibly via co-regulating TLR4/MyD88/NF-κB and Nrf2 signaling pathways

Snow cover duration trends observed at sites and predicted by multiple models

The 30-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models, but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting

Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations

Glycogen synthase kinase-3 (GSK3β), a serine/threonine protein kinase, has been discovered as a novel target for anticancer drugs. Although GSK3β is involved in multiple pathways linked to the etiology of various cancers, no specific GSK3β inhibitor has been authorized for cancer therapy. Most of its inhibitors have toxicity effects therefore, there is a need to develop safe and more potent inhibitors. In this study, a library of 4,222 anti-cancer compounds underwent rigorous computational screening to identify potential candidates for targeting the binding pocket of GSK3β. The screening process involved various stages, including docking-based virtual screening, physicochemical and ADMET analysis, and molecular dynamics simulations. Ultimately, two hit compounds, BMS-754807 and GSK429286A, were identified as having high binding affinities to GSK3β. BMS-754807 and GSK429286A exhibited binding affinities of −11.9, and −9.8 kcal/mol, respectively, which were greater than that of the positive control (−7.6 kcal/mol). Further, molecular dynamics simulations for 100 ns were employed to optimize the interaction between the compounds and GSK3β, and the simulations demonstrated that the interaction was stable and consistent throughout the study. These hits were also anticipated to have good drug-like properties. Finally, this study suggests that BMS-754807 and GSK429286A may undergo experimental validation to evaluate their potential as cancer treatments in clinical settings

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe