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Introduction: Seasonal influenza causes annual school breaks and student absenteeism in Hong Kong schools and kindergartens. This proposal aims to conduct a retrospective cohort study to evaluate the impact of a school-based influenza vaccination (SIV) programme on absenteeism and outbreaks at schools in Hong Kong. Methods: The study will compare schools that implemented the SIV programme with schools that did not. The data will be sourced from school records, encompassing absenteeism records, outbreak reports, and vaccination rates. We will recruit 1000 students from 381 schools and kindergartens in 18 districts of Hong Kong starting June 2024. The primary outcome measures will include absenteeism rates due to influenza and school influenza outbreaks. Secondary outcomes will consist of vaccination coverage rates and the impact of the SIV programme on hospitalisations due to influenza-like illness. A t-test will be conducted to compare the outcomes between schools with and without the SIV programme. Ethics and dissemination: The school completed signing the participants’ informed consent form before reporting the data to us. Our study has been approved by the Hospital Authority Hong Kong West Cluster IRB Committee (IRB No: UW 17–111) and was a subtopic of the research “The estimated age-group specific influenza vaccine coverage rates in Hong Kong and the impact of the school outreach vaccination program”. Trial registration: This study will be retrospectively registered.

Enhancing Autonomous Decision-Making (ADM) for unmanned combat aerial vehicle formations in beyond-visual-range air combat is pivotal for future battlefields, whereas the predominant reinforcement learning technique for ADM has been proven to be inadequately fitting complex tactical Unit Coordination (UC), limiting the integrity of decision-making for formations. This study proposes a knowledge-enhanced ADM method, with a focus on UC, to elevate formation combat effectiveness. The main innovation is integrating data mining technique with tactical knowledge mining and integration. Foremost, based on Frequent Event Arrangement Mining (FEAM) theory, a cross-channel UC knowledge mining method is designed by introducing data flow, which is capable of capturing dynamic coordinative action sequences. Then, a dual-mode knowledge integration method is proposed by employing the Graph Attention Network (GAT) and attenuated structural similarity, bolstering the interplay between autonomous UC tactics fitting and knowledge injection. The experimental results demonstrate that the algorithm surpasses the existing methods, providing more strategic maneuver trajectories and a win rate of more than 90% in different scenarios. The method is promising to augment the autonomous operational capabilities of unmanned formations and drive the evolution of combat effectiveness.

Upper limb motor dysfunction is a major problem in the rehabilitation of patients with stroke. Brain-computer interface (BCI) is a kind of communication system that converts the “ideas” in the brain into instructions and has been used in stroke rehabilitation. This study aimed to investigate the efficacy and safety of BCI in rehabilitation training on upper limb motor function among patients with ischemic stroke.

The monofloral honey from Schefflera octophylla(Lour.) Harms (MH-Sco) are of high economic value due to their rarity and potential medicinal benefits. However, the limited investigations on the relationship of phytogenic components between the plant S. octophylla(P-Sco) and MH-Scohave an impact on MH-Scoauthentication. Herein, the tentative phytogenic markers of MH-Scowere screened by comparing the metabolites of MH-Scoobtained by ultrahigh-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS)-based untargeted metabolomics with the identified phytogenic chemicals from P-Sco. Combined with the mass and NMR spectral information, 3α-hydroxylup-20(29)-ene-23,28-dioic acid (HLEDA) was finally identified as the phytogenic marker of MH-Sco. A targeted ultrahigh-performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS)-based method was established and validated based on the purified monomer standard to measure HLEDA levels in honey samples. HLEDA determined in MH-Scowas with the content from 0.303 to 0.440 mg/kg, while HLEDA was absent in honey samples from other botanical origins, indicating the reliability of HLEDA as a chemical marker in MH-Scoauthentication. This study provides the theoretical basis and industry guidance for honey quality control for commercial consumption.

We studied Gaussian beams with three different partially coherent models, including the Gaussian–Schell model (GSM), Laguerre–Gaussian Schell model (LGSM), and Bessel–Gaussian Schell model (BGSM), propagating through oceanic turbulence. The expressions of average intensity, beam spreading, and beam wander for GSM, LGSM, and BGSM beams in the paraxial channel are derived. We make a contrast for the three models in numerical simulations and find that the GSM beam has smaller spreading than the others, and the LGSM beam needs longer propagation distance to transform into a well-like profile of average intensity than the BGSM beam in the same conditions. The salinity fluctuation has a greater contribution to the wander of LGSM and BGSM beams than that of the temperature fluctuation. Our results can be helpful in the design of an optical wireless communication link operating in oceanic environment.

An injectable and self-adaptive heparin microsphere-based cell scaffold was developed to achieve adipose regeneration. Simultaneously, the cell scaffold exhibited a dynamic architecture, self-regulated glucose levels, sustained insulin delivery, and steady viscoelastic properties for adipogenesis. The dynamic cell scaffold is cross-linked by the boronate–diol interaction among heparin-based microspheres, which have boronate and maltose groups. Because of the boronate–maltose ester bonds, the gelatinous complex would be partially dismantled and readily display glucose-sensitive performance by free glucose via competitive displacement. The dynamic cross-linking heparin microsphere scaffold can deliver the lipogenic drug insulin to enhance lipid filling, which has an impact on fat tissue enhancement. A 4-week in vitrocell culture demonstrated that the dynamic heparin microsphere-based cell scaffold, through loading with insulin, showed significantly higher efficiency in promoting ASC differentiation compared with traditional 3D culture methods. In vivohistological results further demonstrated that there was a significant increase in adipose in the proposed cell scaffold, which proved to be statistically significant compared with traditional biomaterials. Notable stain expression of the FABP4 and PPAR-γ genes was also observed in the dynamic cell scaffold containing insulin, which was more similar to natural fat.

In this paper, HESH, which was a new set of amino acid descriptors including Hydrophobic, Electronic, Steric and Hydrogen bond contribution properties, were derived from multi-dimensional properties of 20 coded amino acids. The quantitative structure-activity relationship (QSAR) of 101 synthetic cationic antimicrobial polypeptides (CAMELs) was then characterized with HESH scales and studied by genetic algorithm-partial least square (GA-PLS) method. It was found that the robust QSAR model constructed with electronic and hydrophobic properties parameters of HESH descriptors was a better one. Through further analysis, electronic and hydrophobic properties of the 3rd, 6th, 7th, 11th and 12th residue of CAMELs sequence made high contribution to antimicrobial potencies. Based on this PLS model, a series of cationic antimicrobial peptides (AMPs), with relatively high antimicrobial activity was designed. Meanwhile, a robust QSAR model with favorable predictive capability for 34 antimicrobial peptides was constructed with HESH descriptors. The results showed that HESH descriptors had many obvious advantages, for it contains abundant information and its physico-chemical characteristics are clear and easily explained. The developed descriptors can be further expanded for the larger sets of biologically activities peptides and can serve as a useful quantitative tool for the rational design and discovery of antibiotics.

Traditional quantitative structure-activity relationship (QSAR) is a term describing a variety of approaches that are of substantial interest for chemistry. Quantitative sequence-activity model (QSAM), applying QSAR strategy to explore sequence-activity/function relationship for biosystems, is greatly meaningful but meanwhile extremely difficult. For biomolecules, high molecular weight, diverse structural morphology and intricate interaction network all bring in traditional QSAR methodologies unprecedented challenges. This article comprehensively reviewed developing process, current state and future perspective of QSAM, concerning its applications into fields of pharmacy, food science, immunology and molecular biology. Besides, discipline-crossing and amalgamation of QSAM with QSAR, bioinformatics and computational biology were also discussed.