Avian eggshells exhibit excellent antimicrobial properties. In this study, we conducted simulation experiments to explore the defense mechanisms of eggshell membranes with regards to their physical features. We developed a mathematical model for the movement of microorganisms and estimated their penetration ratio into eggshell membranes based on several factors, including membrane thickness, microbial size, directional drift, and attachment probability to membrane fibers.

Mid-frequency band gravitational-wav e detectors will be complementary to the existing Earth-based detectors (sensitiv e above 10 Hz or so) and the future space-based detectors such as the Laser Interferometer Space Antenna (LISA), which will be sensitive below around 10 mHz.

In this study, we propose a novel approach that integrates regime-shift detection with a mechanistic model to forecast the peak times of seasonal influenza.

In this paper, the application of the orthogonality sampling method (OSM) to the real-world microwave imaging for identifying location of small anomalies is addressed. In order to show the feasibility and limitation of the OSM, we theoretically prove that the indicator function can be represented in terms of an infinite series of Bessel functions of integer order and the transmitting and receiving signal antenna configurations.

Conclusion: The TD method is a time series analysis that enables early epidemic alert in real-time without relying on past epidemic information. It can be considered as an alternative approach when it is challenging to set an epidemic threshold based on past period information. This situation may arise when there has been a change in the typical seasonal epidemic pattern of various respiratory viruses, including influenza, following the COVID-19 pandemic.

A transmission interval for an infctious disease is important to understand epidemic processes in complex networks. The transmission interval is defined as a time inteval between one person's infection and their infection to another person.

Image based view synthesis using deep neural networks provide novel scene views from a set of captured single View synthesis or multiple images. Multiplane images (MPI) represent scene content as set of RGB？？ planes within a reference Multiplane images view frustum and render novel views by projecting the content into the target viewpoints.

Image super resolution, which obtains high resolution output from a corresponding low resolution image, has been challenging due to inefficiencies in establishing complex high dimensional mapping for massive raw data.

In this paper, we analyze the dynamic bifurcation of the general Brusselator model when the order of reaction is p ∈ (1, ∞). We verify that the Turing instability occurs above the critical control number and obtain a rigorous formula for the bifurcated stable patterns.

In this study, we explore the phenomenological signatures associated with a light fermiophobic Higgs boson, $h_f$, within the type-I two-Higgs-doublet model at the HL-LHC. Our meticulous parameter scan illuminates an intriguing mass range for $m_{h_f}$, spanning [1,10] GeV. This mass range owes its viability to substantial parameter points, largely due to the inherent challenges of detecting the soft decay products of $h_f$ at contemporary high-energy colliders. Given that this light hf ensures $Br(h_f\to\gamma\gamm)\simeq1$, $Br(H^\pm\to h_fW^\pm)\simeq1$, and $M_{H^\pm}？330 GeV$, we propose a golden discovery channel: $pp\to h_fH^\pm\to\gamma\gamma\gamma\gamm l^\pm\nu$, where $l^\pm$includes $e^\pm$ and $\mu^\pm$. However, a significant obstacle arises as the two photons from the $h_f$ decay mostly merge into a single jet due to their proximity within $\Delta R<0.4$. (Skip)