10,542 research outputs found
The Meeting of Acquaintances: A Cost-efficient Authentication Scheme for Light-weight Objects with Transient Trust Level and Plurality Approach
Wireless sensor networks consist of a large number of distributed sensor
nodes so that potential risks are becoming more and more unpredictable. The new
entrants pose the potential risks when they move into the secure zone. To build
a door wall that provides safe and secured for the system, many recent research
works applied the initial authentication process. However, the majority of the
previous articles only focused on the Central Authority (CA) since this leads
to an increase in the computation cost and energy consumption for the specific
cases on the Internet of Things (IoT). Hence, in this article, we will lessen
the importance of these third parties through proposing an enhanced
authentication mechanism that includes key management and evaluation based on
the past interactions to assist the objects joining a secured area without any
nearby CA. We refer to a mobility dataset from CRAWDAD collected at the
University Politehnica of Bucharest and rebuild into a new random dataset
larger than the old one. The new one is an input for a simulated authenticating
algorithm to observe the communication cost and resource usage of devices. Our
proposal helps the authenticating flexible, being strict with unknown devices
into the secured zone. The threshold of maximum friends can modify based on the
optimization of the symmetric-key algorithm to diminish communication costs
(our experimental results compare to previous schemes less than 2000 bits) and
raise flexibility in resource-constrained environments.Comment: 27 page
Pairing effect on the giant dipole resonance width at low temperature
The width of the giant dipole resonance (GDR) at finite temperature T in
Sn-120 is calculated within the Phonon Damping Model including the neutron
thermal pairing gap determined from the modified BCS theory. It is shown that
the effect of thermal pairing causes a smaller GDR width at T below 2 MeV as
compared to the one obtained neglecting pairing. This improves significantly
the agreement between theory and experiment including the most recent data
point at T = 1 MeV.Comment: 8 pages, 5 figures to be published in Physical Review
Learning a local-variable model of aromatic and conjugated systems
A collection of new
approaches to building and training neural
networks, collectively referred to as deep learning, are attracting
attention in theoretical chemistry. Several groups aim to replace
computationally expensive <i>ab initio</i> quantum mechanics
calculations with learned estimators. This raises questions about
the representability of complex quantum chemical systems with neural
networks. Can local-variable models efficiently approximate nonlocal
quantum chemical features? Here, we find that convolutional architectures,
those that only aggregate information locally, cannot efficiently
represent aromaticity and conjugation in large systems. They cannot
represent long-range nonlocality known to be important in quantum
chemistry. This study uses aromatic and conjugated systems computed
from molecule graphs, though reproducing quantum simulations is the
ultimate goal. This task, by definition, is both computable and known
to be important to chemistry. The failure of convolutional architectures
on this focused task calls into question their use in modeling quantum
mechanics. To remedy this heretofore unrecognized deficiency, we introduce
a new architecture that propagates information back and forth in waves
of nonlinear computation. This architecture is still a local-variable
model, and it is both computationally and representationally efficient,
processing molecules in sublinear time with far fewer parameters than
convolutional networks. Wave-like propagation models aromatic and
conjugated systems with high accuracy, and even models the impact
of small structural changes on large molecules. This new architecture
demonstrates that some nonlocal features of quantum chemistry can
be efficiently represented in local variable models
Stability analysis of event-triggered anytime control with multiple control laws
To deal with time-varying processor availability and lossy communication
channels in embedded and networked control systems, one can employ an
event-triggered sequence-based anytime control (E-SAC) algorithm. The main idea
of E-SAC is, when computing resources and measurements are available, to
compute a sequence of tentative control inputs and store them in a buffer for
potential future use. State-dependent Random-time Drift (SRD) approach is often
used to analyse and establish stability properties of such E-SAC algorithms.
However, using SRD, the analysis quickly becomes combinatoric and hence
difficult to extend to more sophisticated E-SAC. In this technical note, we
develop a general model and a new stability analysis for E-SAC based on Markov
jump systems. Using the new stability analysis, stochastic stability conditions
of existing E-SAC are also recovered. In addition, the proposed technique
systematically extends to a more sophisticated E-SAC scheme for which, until
now, no analytical expression had been obtained.Comment: Accepted for publication in IEEE Transactions on Automatic Contro
Chinese Firms’ Political Connection, Ownership, and Financing Constraints
We empirically examine some listed Chinese firms’ political connection, ownership, and financing constraints. Politically-connected firms display no financing constraints whereas firms without connection experience significant constraints. Non-connected family-controlled firms bear greater constraints than non-connected state-owned firms.Political connection; investments; financing constraints; Chinese firms
Child labour in the Mekong Delta, Vietnam
Child labour is a complex challenge facing many countries around the world, including Vietnam. Spurred by the development of the United Nations Convention on the Rights of the Child (1989), it has been a topic of increasing interest for governments and researchers, especially over the past two decades. The focus of many studies on child labour in Vietnam has tended to be urban, particularly as it intersects with the tourism and manufacturing sectors (ILO 2014), street children and child labour (Huong 2016), and the relationship between child labour and child trafficking, human rights and child labour, and the impact of child labour on health and education (Bélanger 2014, Kiss et al 2015, Le and Homel 2015, Bandyopadhyay et al., 2021). Edmonds and colleagues (see for example, Edmonds and Pavcnik (2002b), Edmonds and Turk (2002), Edmonds and Pavcnik (2005)) have also conducted multiple studies on child labour and its correlation with economic development, and the causes, consequences and policies to tackle it. However, less attention has been given to the ongoing problem of child labour in rural areas in Vietnam (exceptions including O’Donnell et. al., 2005 and Trinh, 2020).
Three rural provinces in the Mekong Delta (MD), An Giang, Soc Trang and Kien Giang, are the focus of this study. The thesis systematically re-sequences the complex causes of child labour through the voices of caregivers and authorities. An overview picture of the causes of child labour in rural areas has been presented which has made it easier for policymakers to devise strategies and targets for 251 eliminating child labour. There are no hazardous forms of exploitation found in the study through the voices of the representatives – (grand)parents, but child labour exists many risks for human resources because of the lack of professional training.
Child labour is a challenge to child development in the Mekong Delta of Vietnam. Concerned parties have been aware of the impacts of child labour on the region. However, this knowledge is general. Therefore, an in-depth child labour impact evaluation focusing on the intergenerational cycle of poverty, education, health, and remedial policies needs to be implemented. In addition, raising awareness of child labour must play a principal role in improving the effectiveness of programs for children. The implementation of child labour policies in the long term requires legal bases and support from donation programs
A Novel Murine Myelin Oligodendrocyte Glycoprotein Fusion Protein, MOGtag, Induces Appropriate Autoimmune B Cell Germinal Center Responses And Central Nervous System Autoimmune Disease
The clinical success of B cell-depleting therapies in multiple sclerosis (MS) has identified an important, yet poorly understood pathogenic role for B cells in disease. An animal model of MS, experimental autoimmune encephalomyelitis (EAE), is typically induced through immunization with short myelin-derived peptides. B cells recognize whole proteins and not peptides, therefore their activation and involvement in peptide models of EAE is largely excluded. The goal of this study was to develop a novel fusion myelin protein reagent (MOGtag) to induce autoimmune responses in mice that incorporate T and B cell recognition of antigen. Characterization of the autoimmune response revealed the formation of a T cell-dependent germinal center B cell response. Further, immunization with MOGtag resulted in a chronic disease with evidence of an ongoing immune response, and central nervous system pathology featuring T cell infiltration of white and gray matter as well as formation of meningeal B cell clusters
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