592 research outputs found
Analysis of Age of Information in Non-terrestrial Networks
Non-terrestrial networks (NTN), particularly low Earth orbit (LEO) satellite
networks, have emerged as a promising solution to overcome the limitations of
traditional terrestrial networks in the context of next-generation (6G)
wireless systems. In this paper, we focus on analyzing the timeliness of
information delivery in NTN through the concept of Age of Information (AoI). We
propose an on-off process to approximate the service process between LEO
satellites and a source node located on the Earth's surface. By utilizing
stochastic geometry, we derive a closed-form expression for the time-average
AoI in an NTN. This expression also applies to on-off processes with one
component following an exponential distribution while the other has its
probability density function supported on a bounded interval. Numerical results
validate the accuracy of our analysis and demonstrate the impact of source
status update rate and satellite constellation density on the time-average AoI.
Our work fills a gap in the literature by providing a comprehensive analysis of
AoI in NTN and offers new insights into the performance of LEO satellite
networks
Coverage Analysis for Cellular-Connected Random 3D Mobile UAVs with Directional Antennas
This letter proposes an analytical framework to evaluate the coverage
performance of a cellular-connected unmanned aerial vehicle (UAV) network in
which UAV user equipments (UAV-UEs) are equipped with directional antennas and
move according to a three-dimensional (3D) mobility model. The ground base
stations (GBSs) equipped with practical down-tilted antennas are distributed
according to a Poisson point process (PPP). With tools from stochastic
geometry, we derive the handover probability and coverage probability of a
random UAV-UE under the strongest average received signal strength (RSS)
association strategy. The proposed analytical framework allows to investigate
the effect of UAV-UE antenna beamwidth, mobility speed, cell association, and
vertical motions on both the handover probability and coverage probability. We
conclude that the optimal UAV-UE antenna beamwidth decreases with the GBS
density, and the omnidirectional antenna model is preferred in the sparse
network scenario. What's more, the superiority of the strongest average RSS
association over the nearest association diminishes with the increment of GBS
density.Comment: 5 pages, 5 figures, submitted to IEEE Wireless Communications Letter
On Safeguarding Privacy and Security in the Framework of Federated Learning
Motivated by the advancing computational capacity of wireless end-user
equipment (UE), as well as the increasing concerns about sharing private data,
a new machine learning (ML) paradigm has emerged, namely federated learning
(FL). Specifically, FL allows a decoupling of data provision at UEs and ML
model aggregation at a central unit. By training model locally, FL is capable
of avoiding data leakage from the UEs, thereby preserving privacy and security
to some extend. However, even if raw data are not disclosed from UEs,
individual's private information can still be extracted by some recently
discovered attacks in the FL architecture. In this work, we analyze the privacy
and security issues in FL, and raise several challenges on preserving privacy
and security when designing FL systems. In addition, we provide extensive
simulation results to illustrate the discussed issues and possible solutions.Comment: This paper has been accepted by IEEE Network Magazin
Aptamer-conjugated, fluorescent gold nanorods as potential cancer theradiagnostic agents
Funding for this project was provided by the ERC grant StG242991.GNRs are emerging as a new class of probes for theradiagnostic applications thanks to their unique optical properties. However, the achievement of proper nanoconstructs requires the synthesis of highly pure GNRs with well-defined aspect ratio (AR), in addition to extensive surface chemistry modification to provide them with active targeting and, possibly, multifunctionality. In this work, we refined the method of the seed mediated growth and developed a robust procedure for the fabrication of GNRs with specific AR. We also revealed and characterized unexplored aging phenomena that follow the synthesis and consistently alter GNRs' final AR. Such advances appreciably improved the feasibility of GNRs fabrication and offered useful insights on the growth mechanism. We next produced fluorescent, biocompatible, aptamer-conjugated GNRs by performing ligand exchange followed by bioconjugation to anti-cancer oligonucleotide AS1411. In vitro studies showed that our nanoconstructs selectively target cancer cells while showing negligible cytotoxicity. As a result, our aptamer-conjugated GNRs constitute ideal cancer-selective multifunctional probes and promising candidates as photothermal therapy agents.Publisher PDFPeer reviewe
Ionic high-pressure form of elemental boron
Boron is an element of fascinating chemical complexity. Controversies have
shrouded this element since its discovery was announced in 1808: the new
'element' turned out to be a compound containing less than 60-70 percent of
boron, and it was not until 1909 that 99-percent pure boron was obtained. And
although we now know of at least 16 polymorphs, the stable phase of boron is
not yet experimentally established even at ambient conditions. Boron's
complexities arise from frustration: situated between metals and insulators in
the periodic table, boron has only three valence electrons, which would favour
metallicity, but they are sufficiently localized that insulating states emerge.
However, this subtle balance between metallic and insulating states is easily
shifted by pressure, temperature and impurities. Here we report the results of
high-pressure experiments and ab initio evolutionary crystal structure
predictions that explore the structural stability of boron under pressure and,
strikingly, reveal a partially ionic high-pressure boron phase. This new phase
is stable between 19 and 89 GPa, can be quenched to ambient conditions, and has
a hitherto unknown structure (space group Pnnm, 28 atoms in the unit cell)
consisting of icosahedral B12 clusters and B2 pairs in a NaCl-type arrangement.
We find that the ionicity of the phase affects its electronic bandgap, infrared
adsorption and dielectric constants, and that it arises from the different
electronic properties of the B2 pairs and B12 clusters and the resultant charge
transfer between them.Comment: Published in Nature 453, 863-867 (2009
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
In this paper, to effectively prevent information leakage, we propose a novel
framework based on the concept of differential privacy (DP), in which
artificial noises are added to the parameters at the clients side before
aggregating, namely, noising before model aggregation FL (NbAFL). First, we
prove that the NbAFL can satisfy DP under distinct protection levels by
properly adapting different variances of artificial noises. Then we develop a
theoretical convergence bound of the loss function of the trained FL model in
the NbAFL. Specifically, the theoretical bound reveals the following three key
properties: 1) There is a tradeoff between the convergence performance and
privacy protection levels, i.e., a better convergence performance leads to a
lower protection level; 2) Given a fixed privacy protection level, increasing
the number of overall clients participating in FL can improve the
convergence performance; 3) There is an optimal number of maximum aggregation
times (communication rounds) in terms of convergence performance for a given
protection level. Furthermore, we propose a -random scheduling strategy,
where () clients are randomly selected from the overall clients
to participate in each aggregation. We also develop the corresponding
convergence bound of the loss function in this case and the -random
scheduling strategy can also retain the above three properties. Moreover, we
find that there is an optimal that achieves the best convergence
performance at a fixed privacy level. Evaluations demonstrate that our
theoretical results are consistent with simulations, thereby facilitating the
designs on various privacy-preserving FL algorithms with different tradeoff
requirements on convergence performance and privacy levels
Kids Into Health Careers: A Rural Initiative
Abstract
Purpose: To describe a project that introduces middle school and high school students living in Pennsylvania’s rural geographic regions to nursing careers through outreach extended to students regardless of gender, ethnicity, or socioeconomic status.
Method: The authors employed many strategies to inform students about careers in nursing. The methods included: working with guidance counselors, participating in community health fairs, taking part in school health career fairs, collaborating with Area Health Education Centers, serving on volunteer local education advisory boards, developing a health careers resource guide, and establishing a rural health advisory board.
Findings: Developing developmentally appropriate programs may have the potential to pique interest in nursing careers in children of all ages, preschool through high school. Publicity is needed to alert the community of kids into health care career programs. Timing is essential when planning visits to discuss health care professions opportunities with middle and high school students. It is important to increase the number of high school student contacts during the fall months. Targeting high school seniors is particularly important as they begin the college applications process and determine which school will best meet their educational goals.
Conclusions: Outcome measures to determine the success of health career programs for students in preschool through high school are needed. Evaluation methods will be continued over the coming years to assess effectiveness
Semantic Entropy Can Simultaneously Benefit Transmission Efficiency and Channel Security of Wireless Semantic Communications
Recently proliferated deep learning-based semantic communications (DLSC)
focus on how transmitted symbols efficiently convey a desired meaning to the
destination. However, the sensitivity of neural models and the openness of
wireless channels cause the DLSC system to be extremely fragile to various
malicious attacks. This inspires us to ask a question: "Can we further exploit
the advantages of transmission efficiency in wireless semantic communications
while also alleviating its security disadvantages?". Keeping this in mind, we
propose SemEntropy, a novel method that answers the above question by exploring
the semantics of data for both adaptive transmission and physical layer
encryption. Specifically, we first introduce semantic entropy, which indicates
the expectation of various semantic scores regarding the transmission goal of
the DLSC. Equipped with such semantic entropy, we can dynamically assign
informative semantics to Orthogonal Frequency Division Multiplexing (OFDM)
subcarriers with better channel conditions in a fine-grained manner. We also
use the entropy to guide semantic key generation to safeguard communications
over open wireless channels. By doing so, both transmission efficiency and
channel security can be simultaneously improved. Extensive experiments over
various benchmarks show the effectiveness of the proposed SemEntropy. We
discuss the reason why our proposed method benefits secure transmission of
DLSC, and also give some interesting findings, e.g., SemEntropy can keep the
semantic accuracy remain 95% with 60% less transmission.Comment: 13 pages, 12 figure
Central Venous Pressure and Pulmonary Capillary Wedge Pressure
Heart-failure phenotypes include pulmonary and systemic venous congestion. Traditional heart-failure classification systems include the Forrester hemodynamic subsets, which use 2 indices: pulmonary capillary wedge pressure (PCWP) and cardiac index. We hypothesized that changes in PCWP and central venous pressure (CVP), and in the phenotypes of heart failure, might be better evaluated by cardiovascular modeling. Therefore, we developed a lumped-parameter cardiovascular model and analyzed forms of heart failure in which the right and left ventricles failed disproportionately (discordant ventricular failure) versus equally (concordant failure). At least 10 modeling analyses were carried out to the equilibrium state. Acute discordant pump failure was characterized by a “passive” volume movement, with fluid accumulation and pressure elevation in the circuit upstream of the failed pump. In biventricular failure, less volume was mobilized. These findings negate the prevalent teaching that pulmonary congestion in left ventricular failure results primarily from the “backing up” of elevated left ventricular filling pressure. They also reveal a limitation of the Forrester classification: that PCWP and cardiac index are not independent indices of circulation.
Herein, we propose a system for classifying heart-failure phenotypes on the basis of discordant or concordant heart failure. A surrogate marker, PCWP–CVP separation, in a simplified situation without complex valvular or pulmonary disease, shows that discordant left and right ventricular failures are characterized by differences of ≥4 and ≤0 mmHg, respectively. We validated the proposed model and classification system by using published data on patients with acute and chronic heart failure
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