Deep neck infections (DNIs) such as parotid abscesses are medical emergencies with a seemingly different etiology and treatment course from other DNIs. We sought to confirm this in the present retrospective population-based cohort study. Between Augu...
In light of an upcoming series of missions beyond low Earth orbit (LEO) through NASA’s Artemis program and the potential establishment of bases on the Moon and Mars, the effects of the deep space environment on biology need to be examined and p...
The deterioration of the global climate and accelerated urbanization have led to intense pressure on surface space resources. As a strategic development field, deep underground space has become a crucial direction for alleviating human habitation pre...
Deep space exploration missions face technical challenges such as long-distance communication delays and high-precision autonomous positioning. Traditional ground-based telemetry and control as well as inertial navigation schemes struggle to meet mis...
This paper investigates the use of pulsar-based navigation for deep-space CubeSats. A novel approach for dealing with the onboard computation of navigational solutions and timekeeping capabilities of a spacecraft in a deep-space cruise is shown, and...
Deep space navigation, defined as spacecraft position tracking beyond the lunar orbit, presents significant challenges due to the extremely weak Global Navigation Satellite System (GNSS) signals and severe signal attenuation over interplanetary dista...
Detecting celestial bodies while in deep-space travel is a critical task for the correct execution of space missions. Major bodies such as planets are bright and therefore easy to observe, while small bodies can be faint and therefore difficult to ob...
Infections of the deep neck spaces often present a clinical challenge for the ENT surgeon. Management of these complex suppurations of the neck requires in fact a multidisciplinary approach due to possible complications like mediastinitis, septic sho...
Communications in delay-tolerant networking (DTN) environments like deep space face significant challenges due to immense distances and the intermittent nature of links. Overcoming these issues requires moving beyond the assumptions of immediacy and...
This research unveils a cutting-edge navigation system for deep space missions that utilizes cosmic microwave background (CMB) sensor readings to enhance spacecraft positioning and velocity estimation accuracy significantly. By exploiting the Doppler...
As the field of deep learning experiences a meteoric rise, the urgency to decipher the complex geometric properties of feature spaces, which underlie the effectiveness of diverse learning algorithms and optimization techniques, has become paramount....
Deep space exploration offers the most profound opportunity for the expansion of humanity and our understanding of the universe but remains extremely challenging. Progress will continue to be paced by uncrewed missions followed up by crewed missions...
With the rapid development of space laser communication and deep-space exploration, Deep Space Optical Sensor Networks (DSOSN) have become a vital support for deep-space information transmission. Conventional Directed Diffusion (DD) adopts fixed sing...
Recent efforts in on-orbit servicing, manufacturing, and debris removal have accentuated some of the challenges related to close-proximity space manipulation. Orbital debris threatens future space endeavors driving active removal missions. Additional...
Training deep learning models requires having the right data for the problem and understanding both your data and the models’ performance on that data. Training deep learning models is difficult when data are limited, so in this paper, we seek...
Deep space missions face challenges in guidance, navigation, and control due to subtle non-gravitational forces, such as the Pioneer Anomaly—an unexplained acceleration toward the Sun observed in Pioneer 10 and 11. The most plausible cause is t...
Complex and unknown terrains in deep space exploration present great challenges to existing exploration robots. In this paper, a multi-mode motion spherical robot with flexible motion and strong environmental adaptability is presented. The spherical...
Most text classification systems use machine learning algorithms; among these, naïve Bayes and support vector machine algorithms adapted to handle text data afford reasonable performance. Recently, given developments in deep learning technology, seve...
Predicting cellular responses to perturbations is an unsolved problem in biology. Traditional approaches assume that different cell types respond similarly to perturbations. However, this assumption does not take into account the context of genome in...
The complex and dynamic space environment is both exciting and challenging in this NewSpace era. In particular, Low-Earth Orbits are being realigned and reinvented for various purposes using suitable technological advancement. This paper is focused o...
It is of utmost importance to develop a computational method for accurate prediction of antioxidants, as they play a vital role in the prevention of several diseases caused by oxidative stress. In this correspondence, we present an effective computat...
Existing low-light image enhancement methods often struggle to effectively enhance space targets in deep-space contexts due to the effects of extremely low illumination, stellar stray light, and Earth halos. This work proposes a low-light image enhan...
The COVID-19 pandemic has presented a unique challenge for physicians worldwide, as they grapple with limited data and uncertainty in diagnosing and predicting disease outcomes. In such dire circumstances, the need for innovative methods that can aid...
The cellular functions are executed by biological macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving the conformational continuum of important biomolecular complexes at the a...
In the field of direction of arrival (DOA) estimation for coherent sources, subspace-based model-driven methods exhibit increased computational complexity due to the requirement for eigenvalue decomposition. In this paper, we propose a new neural net...
In recent years, deep learning methods have been used with increasing frequency to solve architectural design problems. This paper aims to study the spatial functional layout of deep learning-assisted generation subway stations. Using the PointNet++...
One of the basic requirements of an automated parking system is to quickly and accurately detect parking spaces. With the development of deep convolutional neural networks, parking space detection systems are becoming increasingly mature. However, th...
Optical communication is a critical technology for future deep space exploration, offering substantial advantages in transmission capacity and spectrum utilization. This paper establishes a comprehensive theoretical framework for avalanche photodiode...
In space environments, microgravity, high radiation, and weak magnetic fields induce behavioral alterations in animals, resulting in erratic movement patterns that complicate tracking. These challenges impede accurate behavioral analysis, especially...
Very Long Baseline Interferometry (VLBI) solution can yield accurate information of angular position, and has been successfully used in the field of deep space exploration, such as astrophysics, imaging, detector positioning, and so on. The increase...
This paper presents a novel object transportation method using deep reinforcement learning (DRL) and the task space decomposition (TSD) method. Most previous studies on DRL-based object transportation worked well only in the specific environment wher...
With the development of technology and methodologies, Raman spectrometers are becoming efficient candidate payloads for planetary materials characterizations in deep space exploration missions. The National Aeronautics and Space Administration (NASA)...
Due to enclosed space, long evacuation distances, and complex path structures, key nodes in deep underground spaces are prone to forming bottlenecks during fire evacuation. To collect evacuation behavior data at potential bottlenecks, an interactive...
Sketch-based 3D model retrieval has become an important research topic in many applications, such as computer graphics and computer-aided design. Although sketches and 3D models have huge interdomain visual perception discrepancies, and sketches of t...
A unique End-of-Life (EOL) Deep Space View Test (DSVT) was performed on 27 November 2021 for the Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) onboard the first EUMETSAT MetOp-A satellite in the deorbiting proce...
The COVID-19 pandemic has fundamentally transformed residential spaces, yet traditional survey-based approaches face limitations in objectively capturing these changes. This study investigates residential design trends in the Post-pandemic era, defin...
The application of space robotic manipulators and heightened autonomy for In-Orbit Servicing (IOS) represents a paramount pursuit for leading space agencies, given the substantial threat posed by space debris to operational satellites and forthcoming...
Deep Reinforcement Learning (DRL) algorithms often exhibit significant performance variability across different training runs, even with identical settings. This paper investigates the hypothesis that a key contributor to this variability is the dive...
Free-space optical communication (FSO) technology has wide prospects in deep space exploration, but it will encounter coronal turbulence during superior solar conjunction, and solar scintillation will seriously affect the communication quality. In th...
Artificial Intelligence of things (AIoT) is the combination of Artificial Intelligence (AI) technologies and the Internet of Things (IoT) infrastructure. AI deals with the devices’ learning process to acquire knowledge from data and experience,...
The stability of surrounding rock is the basic guarantee of underground space engineering safety. The large deformation of a roadway’s surrounding rock is a very common phenomenon during the underground excavation of coal mine roadways or coal...
Lossless image compression is pivotal for deep-space exploration. Considering the requirements of deep-space exploration for a high compression ratio and real-time processing, traditional image compression algorithms have garnered significant attenti...
The remarkably long distances covered by deep space probes result in extremely weak downlink signals, which poses great challenges for ground measurement systems. In the current climate, improving the comprehensive utilization of downlink signal powe...
During the on-orbit operation task of the space manipulator, some specific scenarios require strict constraints on both the position and orientation of the end-effector, such as refueling and auxiliary docking. To this end, a novel motion planning ap...
Relay-aided free-space optical (FSO) communication systems have the ability of mitigating the adverse effects of link disruption by dividing a long link into several short links. In order to solve the relay selection (RS) problem in a decode and forw...
The space information networks (SIN) have a series of characteristics, such as strong heterogeneity, multiple types of resources, and difficulty in management. Aiming at the problem of resource allocation in SIN, this paper firstly establishes a hier...
Precise orbit determination for multi-spacecraft deep space missions faces challenges including long communication delays, sparse tracking, dynamic model uncertainties, and inefficient data fusion. Presenting a hybrid estimation architecture, this st...
With excellent economy and properties, pressureless sintered micron silver has been regarded as an environmentally friendly interconnection material. In order to promote its reliable application in deep space exploration considering the porous micros...
Anthropomorphic robotic hands are designed to attain dexterous movements and flexibility much like human hands. Achieving human-like object manipulation remains a challenge especially due to the control complexity of the anthropomorphic robotic hand...
Space situational awareness (SSA) is becoming increasingly challenging with the proliferation of resident space objects (RSOs), ranging from CubeSats to mega-constellations. Sensors within the United States Space Surveillance Network are tasked to re...
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