Real-time surveillance systems with green wireless sensor networks (WSNs) are vital for maintaining high energy efficiency in many situations. This paper considers a scenario utilizing green WSNs to ...monitor the situation of Internet of Things (IoT), which constitute one of the most crucial sources of electricity consumption in information and communications technologies (ICT). More specifically, we focus on optimizing the cluster structure to minimize the delay and energy consumption for aggregation convergecast in green WSNs. We first find the optimal value of the network cluster radius for minimizing the delay through theoretical analysis. We then propose a novel cluster network architecture in which clusters that are far from the sink are small, allowing inter-cluster data aggregation to be processed earlier, and clusters that are near the sink are relatively large to allow more time for intra-cluster data aggregation. Hence, the sensor nodes can be scheduled in consecutive time slots to reduce the number of state transitions, consequently achieving the goal of minimizing both delay and energy consumption. Simulation results indicate that the proposed Algorithm outperforms previously reported solutions in terms of both schedule length and lifetime, thereby demonstrating its effectiveness.
Let
a
>
0
,
b
>
0
and
V
(
x
)
≥
0
be a coercive function in
R
2
. We study the solutions with normalized
L
2
-norm for the following Kirchhoff type equation
-
a
+
b
∫
R
2
|
∇
u
|
2
d
x
Δ
u
+
V
(
x
...)
u
=
β
|
u
|
2
u
+
λ
u
on a suitable weighted Sobolev space
H
=
u
∈
H
1
(
R
2
)
:
∫
R
2
V
(
x
)
u
2
d
x
<
∞
.
Our aim is to investigate the limit behaviors of the solutions with normalized
L
2
-norm for this equation as
(
a
,
b
)
→
(
0
,
0
)
. Moreover, the uniqueness of the solution with normalized
L
2
-norm for this equation is also discussed for
a
,
b
close to 0
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has lasted more than 2 years with over 260 million infections and 5 million deaths worldwide as of November 2021. To combat ...the virus, monoclonal antibodies blocking the virus binding to human receptor, the angiotensin converting enzyme 2 (ACE2), have been approved to treat the infected patients. Inactivated whole virus or the full-length virus spike encoding adenovirus or mRNA vaccines are being used to immunize the public. However, SARS-CoV-2 variants are emerging. These, to some extent, escape neutralization by the therapeutic antibodies and vaccine-induced immunity. Thus, breakthrough infections by SARS-CoV-2 variants have been reported in previously virus-infected or fully vaccinated individuals. The receptor binding domain (RBD) of the virus spike protein reacts with host ACE2, leading to the entry of the virus into the cell. It is also the major antigenic site of the virus, with more than 90% of broadly neutralizing antibodies from either infected patients or vaccinated individuals targeting the spike RBD. Therefore, mutations in the RBD region are effective ways for SARS-CoV-2 variants to gain infectivity and escape the immunity built up by the original vaccines or infections. In this review, we focus on the impact of RBD mutations in SARS-CoV-2 variants of concern (VOC) and variants of interest (VOI) on ACE2 binding affinity and escape of serum antibody neutralization. We also provide protein structure models to show how the VOC and VOI RBD mutations affect ACE2 binding and allow escape of the virus from the therapeutic antibody, bamlanivimab.
This study investigates the correlation between previous coal mine safety policies and accidents in China. Data on coal mine accidents and government regulatory information from 2008 to 2021 are ...collected. The characteristics of coal mine accidents are analyzed, and safety policy indexes are identified. An ordinary least squares (OLS) regression model is established to quantitatively analyze the correlation between accidents and safety policy. The study finds that safety policies have some impact on accident occurrence in coal mines. Although there has been a decrease in accidents and deaths over time, higher mortality rates are observed during periods of increased production intensity and on weekends. Gas accidents are the most common, followed by roof and flood accidents. The study concludes that national safety policies with wider coverage and a stronger system are effective in preventing accidents, but caution should be exercised to avoid reduced vigilance with decreasing death rates.
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Four-dimensional (4D) printing, a new technology emerged from additive manufacturing (3D printing), is widely known for its capability of programming post-fabrication shape-changing into artifacts. ...Fused deposition modeling (FDM)-based 4D printing, in particular, uses thermoplastics to produce artifacts and requires computational analysis to assist the design processes of complex geometries. However, these artifacts are weak against structural loads, and the design quality can be limited by less accurate material models and numerical simulations. To address these issues, this paper propounds a composite structure design made of two materials – polylactic acid (PLA) and carbon fiber reinforced PLA (CFPLA) – to increase the structural strength of 4D printed artifacts and a workflow composed of several physical experiments and series of dynamic mechanical analysis (DMA) to characterize materials. We apply this workflow to 3D printed samples fabricated with different printed parameters to accurately characterize the materials and implement a sequential finite element analysis (FEA) to achieve accurate simulations. The accuracy of deformation induced by the triggering process is both computationally and experimentally verified with several creative design examples and is measured to be at least 95%, with a confidence interval of (0.972,0.985). We believe the presented workflow is essential to the combination of geometry, material mechanism and design, and has various potential applications.
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•A novel workflow is proposed for forward design, with accurate material property characterization and precise FEA simulation. This workflow supports robust and accurate fabrication of the designed object through an iterative optimization process and accurate control of the final configuration.•The material properties of 3D printing polymers, including both PLA and CFPLA, are characterized in a precise way based on the DMA experiments. The characterization results are effectively incorporated into FEA with accurate mathematical models.•A sequential FEA is developed to achieve accurate simulation results, considering both the residual stress releasing and the body force creeping. We simulate these two processes in a sequence to precisely derive the final deformation of the fabricated product.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Multi-Access Edge Computing (MEC) is a promising paradigm that providing cloud-like service for handling the high-complexity and latency-sensitive applications on user equipment (UE) via computation ...offloading. However, the execution reliability is rarely considered in current MEC studies, which is an important factor to guarantee the quality of service (QoS). For that, this paper considers an energy-saving offloading to satisfy the reliability and latency requirements of the application. Specifically, we formulate an optimization problem to minimize the UE's energy consumption with reliability and latency constraints. To tackle this NP-hard problem, we first divide the entire application into multiple directed-acyclic-graph-(DAG)-based subtasks, where the subtask can be executed on the UE locally or MEC server remotely. Then, we decompose the overall reliability and latency requirements into multiple constraints for each subtask. Finally, we propose a fast heuristic algorithm to find a solution satisfying the constraints. Simulation results demonstrate the proposed algorithm obtains lower energy consumption compared with the local execution and random assignment and costs less runtime compared with the greedy algorithm.
The newly emerging variants of SARS-CoV-2 from South Africa (B.1.351/501Y.V2) and Brazil (P.1/501Y.V3) have led to a higher infection rate and reinfection of COVID-19 patients. We found that the ...mutations K417N, E484K, and N501Y within the receptor-binding domains (RBDs) of the virus could confer ~2-fold higher binding affinity to the human receptor, angiotensin converting enzyme 2 (ACE2), compared to the wildtype RBD. The mutated version of RBD also completely abolishes the binding of bamlanivimab, a therapeutic antibody, in vitro. Detailed analysis shows that the ~10-fold gain of binding affinity between ACE2 and Y501-RBD, which also exits in the high contagious variant B.1.1.7/501Y.V1 from the United Kingdom, is compromised by additional introduction of the K417/N/T mutation. Mutation of E484K leads to the loss of bamlanivimab binding to RBD, although this mutation does not affect the binding between RBD and ACE2.
Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile ...charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger's limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network's Quality of Service (QoS). In this paper, we propose a mobile charger's scheduling algorithm to mitigate the data loss of network by considering the node's criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node's connectivity contribution, which is computed as a summation of node's neighbor dissimilarity. Furthermore, to reflect the node's charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node's consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger's traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one.
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