Evaluation of medical services from the perspective of COVID-19 vaccine demand satisfaction in Hangzhou, China

The outbreak of COVID-19 has had a huge global impact, and it continues to test the resilience of medical services to emergencies worldwide. In the current post-epidemic era, vaccination has become a highly effective strategy to prevent the spread of COVID-19. However, using conventional mathematical models to evaluate the spatial distribution of medical resources, including vaccination, ignore people\u27s behaviors and choices and make simplifications to the real world. In this study, we use an enhanced model based on the Theory of People Behavior (TPB) to perform a macro analysis of the satisfaction ability of medical resources for vaccination in Hangzhou, China, and attribute the city to a three-level structure. According to the allocation, the supply capacity of vaccination sites is calculated and divided into four categories (good, normal, not bad, and bad). Meanwhile, we raise an assumption based on the result and the general development law of the city and analyze the reasons for the impact of personal behavior on the spatial distribution of medical resources, as well as the relationship between the demand distribution and spatial distribution of medical resources and future development strategies. It is considered that the overall medical resources, especially vaccination in Hangzhou, feature the situation of central supply overflow, and are found to hardly meet the needs of population points in surrounding areas, requiring a more flexible strategy to allocate facilities in these areas

Spontaneous electric-polarization topology in confined ferroelectric nematics

Topological spin and polar textures have fascinated people in different areas of physics and technologies. However, the observations are limited in magnetic and solid-state ferroelectric systems. Ferroelectric nematic is the first liquid-state ferroelectric that would carry many possibilities of spatially distributed polarization fields. Contrary to traditional magnetic or crystalline systems, anisotropic liquid crystal interactions can compete with the polarization counterparts, thereby setting a challenge in understating their interplays and the resultant topologies. Here, we discover chiral polarization meron-like structures during the emergence and growth of quasi-2D ferroelectric nematic domains, which are visualized by fluorescence confocal polarizing microscopy and second harmonic generation microscopies. Such micrometre-scale polarization textures are the modified electric variants of the magnetic merons. Unlike the conventional liquid crystal textures driven solely by the elasticity, the polarization field puts additional topological constraints, e.g., head-to-tail asymmetry, to the systems and results in a variety of previously unidentified polar topological patterns. The chirality can emerge spontaneously in polar textures and can be additionally biased by introducing chiral dopants. An extended mean-field modelling for the ferroelectric nematics reveals that the polarization strength of systems plays a dedicated role in determining polarization topology, providing a guide for exploring diverse polar textures in strongly-polarized liquid crystals

Collective and non-collective molecular dynamics in a ferroelectric nematic liquid crystal studied by broadband dielectric spectroscopy

A great deal of effort has been recently devoted to the study of dielectric relaxation processes in ferroelectric nematic liquid crystals, yet their interpretation remains unclear. In this work, we present the results of broadband dielectric spectroscopy experiments of a prototypical ferroelectric nematogen in the frequency range 10 Hz-110 MHz at different electrode separations and under the application of DC bias fields. The results evidence a complex behavior in all phases due to the magnitude of polar correlations in these systems. The observed modes have been assigned to different relaxation mechanisms based on existing theoretical frameworks.Comment: The following article has been submitted to The Journal of Chemical Physics. After it is published, it will be found at https://pubs.aip.org/aip/jc

Detection of Electromagnetic Seismic Precursors from Swarm Data by Enhanced Martingale Analytics

The detection of seismic activity precursors as part of an alarm system will provide opportunities for minimization of the social and economic impact caused by earthquakes. It has long been envisaged, and a growing body of empirical evidence suggests that the Earth’s electromagnetic field could contain precursors to seismic events. The ability to capture and monitor electromagnetic field activity has increased in the past years as more sensors and methodologies emerge. Missions such as Swarm have enabled researchers to access near-continuous observations of electromagnetic activity at second intervals, allowing for more detailed studies on weather and earthquakes. In this paper, we present an approach designed to detect anomalies in electromagnetic field data from Swarm satellites. This works towards developing a continuous and effective monitoring system of seismic activities based on SWARM measurements. We develop an enhanced form of a probabilistic model based on the Martingale theories that allow for testing the null hypothesis to indicate abnormal changes in electromagnetic field activity. We evaluate this enhanced approach in two experiments. Firstly, we perform a quantitative comparison on well-understood and popular benchmark datasets alongside the conventional approach. We find that the enhanced version produces more accurate anomaly detection overall. Secondly, we use three case studies of seismic activity (namely, earthquakes in Mexico, Greece, and Croatia) to assess our approach and the results show that our method can detect anomalous phenomena in the electromagnetic data

Toward Reproducing Network Research Results Using Large Language Models

Reproducing research results in the networking community is important for both academia and industry. The current best practice typically resorts to three approaches: (1) looking for publicly available prototypes; (2) contacting the authors to get a private prototype; and (3) manually implementing a prototype following the description of the publication. However, most published network research does not have public prototypes and private prototypes are hard to get. As such, most reproducing efforts are spent on manual implementation based on the publications, which is both time and labor consuming and error-prone. In this paper, we boldly propose reproducing network research results using the emerging large language models (LLMs). In particular, we first prove its feasibility with a small-scale experiment, in which four students with essential networking knowledge each reproduces a different networking system published in prominent conferences and journals by prompt engineering ChatGPT. We report the experiment's observations and lessons and discuss future open research questions of this proposal. This work raises no ethical issue

Characterization of physicochemical properties of ivy nanoparticles for cosmetic application

Background Naturally occurring nanoparticles isolated from English ivy (Hedera helix) have previously been proposed as an alternative to metallic nanoparticles as sunscreen fillers due to their effective UV extinction property, low toxicity and potential biodegradability. Methods This study focused on analyzing the physicochemical properties of the ivy nanoparticles, specifically, those parameters which are crucial for use as sunscreen fillers, such as pH, temperature, and UV irradiation. The visual transparency and cytotoxicity of ivy nanoparticles were also investigated comparing them with other metal oxide nanoparticles. Results Results from this study demonstrated that, after treatment at 100°C, there was a clear increase in the UV extinction spectra of the ivy nanoparticles caused by the partial decomposition. In addition, the UVA extinction spectra of the ivy nanoparticles gradually reduced slightly with the decrease of pH values in solvents. Prolonged UV irradiation indicated that the influence of UV light on the stability of the ivy nanoparticle was limited and time-independent. Compared to TiO2 and ZnO nanoparticles, ivy nanoparticles showed better visual transparency. Methylthiazol tetrazolium assay demonstrated that ivy nanoparticles exhibited lower cytotoxicity than the other two types of nanoparticles. Results also suggested that protein played an important role in modulating the three-dimensional structure of the ivy nanoparticles. Conclusions Based on the results from this study it can be concluded that the ivy nanoparticles are able to maintain their UV protective capability at wide range of temperature and pH values, further demonstrating their potential as an alternative to replace currently available metal oxide nanoparticles in sunscreen applications. doi:10.1186/1477-3155-11-

Noncontact Speckle Contrast Diffuse Correlation Tomography of Blood Flow Distributions in Tissues with Arbitrary Geometries

A noncontact electron multiplying charge-coupled-device (EMCCD)-based speckle contrast diffuse correlation tomography (scDCT) technology has been recently developed in our laboratory, allowing for noninvasive three-dimensional measurement of tissue blood flow distributions. One major remaining constraint in the scDCT is the assumption of a semi-infinite tissue volume with a flat surface, which affects the image reconstruction accuracy for tissues with irregular geometries. An advanced photometric stereo technique (PST) was integrated into the scDCT system to obtain the surface geometry in real time for image reconstruction. Computer simulations demonstrated that a priori knowledge of tissue surface geometry is crucial for precisely reconstructing the anomaly with blood flow contrast. Importantly, the innovative integration design with one single-EMCCD camera for both PST and scDCT data collection obviates the need for offline alignment of sources and detectors on the tissue boundary. The in vivo imaging capability of the updated scDCT is demonstrated by imaging dynamic changes in forearm blood flow distribution during a cuff-occlusion procedure. The feasibility and safety in clinical use are evidenced by intraoperative imaging of mastectomy skin flaps and comparison with fluorescence angiography