4 research outputs found
Using artificial neural networks to forecast monthly rainfall and runoff over the central highland, Vietnam
Event-triggered anytime control with two controllers
In networked and multi-tasking environments, measurement data and processing resources may not be available at times when control calculations need to be executed. In this paper, we present an anytime algorithm which features two control policies: a coarse policy and a fine policy. The fine control policy requires more processing resources than the coarse policy. With this scheme, the network and processing resources can be used more efficiently, and performance can be improved. Specifically, for a given packet dropout rate and process availability which are independent and identically distributed (i.i.d.), the proposed two-controller scheme achieves better closed-loop performance with a lower channel utilization than alternative control formulations
A behavior-based malware spreading model for vehicle-to-vehicle communications in VANET networks
Network attacking using malware has become very popular on the Internet and in many other networks, namely Vehicular Ad-hoc Network (VANET) networks. It is required to have the model describing the malware spreading based on factors, which directly affect this process to limit its influences. In this paper, we propose a mathematical model called SEIR-S (Susceptible– Exposed–Infectious–Recovered–Susceptible) based on the characteristics of the VANET network and the well-known disease-spreading model SIR (Susceptible–Infectious–Recovered). We take into account possible behaviors of malware and provide the corresponding states to vehicles: Susceptible (S), Exposed (E), Infectious (I), Recovered (R). We evaluate the basic reproduction number R0 of the model and perform a stability analysis of the proposed model. The results show that, when R0 < 1, the malware spreading will gradually decrease, and, when R0 > 1, that spreading cannot be extinguished. We also point out the condition that we can control the endemic in the VANET network. In addition, the correctness of the proposed model is verified using both numerical analysis and agent-based simulation on NetLogo. © 2021 by the authors. Licensee MDPI, Basel, Switzerland
Genotype-phenotype correlations and novel molecular insights into the DHX30-associated neurodevelopmental disorders
Background We aimed to define the clinical and variant spectrum and to provide novel molecular insights into the DHX30-associated neurodevelopmental disorder. Methods Clinical and genetic data from affected individuals were collected through Facebook-based family support group, GeneMatcher, and our network of collaborators. We investigated the impact of novel missense variants with respect to ATPase and helicase activity, stress granule (SG) formation, global translation, and their effect on embryonic development in zebrafish. SG formation was additionally analyzed in CRISPR/Cas9-mediated DHX30-deficient HEK293T and zebrafish models, along with in vivo behavioral assays. Results We identified 25 previously unreported individuals, ten of whom carry novel variants, two of which are recurrent, and provide evidence of gonadal mosaicism in one family. All 19 individuals harboring heterozygous missense variants within helicase core motifs (HCMs) have global developmental delay, intellectual disability, severe speech impairment, and gait abnormalities. These variants impair the ATPase and helicase activity of DHX30, trigger SG formation, interfere with global translation, and cause developmental defects in a zebrafish model. Notably, 4 individuals harboring heterozygous variants resulting either in haploinsufficiency or truncated proteins presented with a milder clinical course, similar to an individual harboring a de novo mosaic HCM missense variant. Functionally, we established DHX30 as an ATP-dependent RNA helicase and as an evolutionary conserved factor in SG assembly. Based on the clinical course, the variant location, and type we establish two distinct clinical subtypes. DHX30 loss-of-function variants cause a milder phenotype whereas a severe phenotype is caused by HCM missense variants that, in addition to the loss of ATPase and helicase activity, lead to a detrimental gain-of-function with respect to SG formation. Behavioral characterization of dhx30-deficient zebrafish revealed altered sleep-wake activity and social interaction, partially resembling the human phenotype. Conclusions Our study highlights the usefulness of social media to define novel Mendelian disorders and exemplifies how functional analyses accompanied by clinical and genetic findings can define clinically distinct subtypes for ultra-rare disorders. Such approaches require close interdisciplinary collaboration between families/legal representatives of the affected individuals, clinicians, molecular genetics diagnostic laboratories, and research laboratories