Structural Invariants for the Verification of Systems with Parameterized Architectures
Ontology highlight
ABSTRACT:
SUBMITTER: Biere A
PROVIDER: S-EPMC7439742 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The geometric designs of MEMS devices can profoundly impact their physical properties and eventual performances. However, it is challenging for researchers to rationally consider a large number of possible designs, as it would be very time- and resource-consuming to study all these cases using numerical simulation. In this paper, we report the use of deep learning techniques to accelerate the MEMS design cycle by quickly and accurately predicting the physical properties of numerous design candidates with vastly different geometric features. Design candidates are represented in a nonparameterized, topologically unconstrained form using pixelated black-and-white images. After sufficient training, a deep neural network can quickly calculate the physical properties of interest with good accuracy without using conventional numerical tools such as finite element analysis. As an example, we apply our deep learning approach in the prediction of the modal frequency and quality factor of disk-shaped microscale resonators. With reasonable training, our deep learning neural network becomes a high-speed, high-accuracy calculator: it can identify the flexural mode frequency and the quality factor 4.6 × 103 times and 2.6 × 104 times faster, respectively, than conventional numerical simulation packages, with good accuracies of 98.8 ± 1.6% and 96.8 ± 3.1%, respectively. When simultaneously predicting the frequency and the quality factor, up to ~96.0% of the total computation time can be saved during the design process. The proposed technique can rapidly screen over thousands of design candidates and promotes experience-free and data-driven MEMS structural designs.
| S-EPMC9424241 | biostudies-literature
Project description:Abstract Modulating temperature fields is indispensable for advancing modern technologies: space probes, electronic packing, and implantable medical devices, to name a few. Bio-inspired thermal regulation achieved via fluid flow within a network of embedded vesicles is notably desirable for slender synthetic material systems. This far-reaching study—availing theory, numerics, and experiments—reveals a counter-intuitive yet fundamental property of vascular-based fluid-flow-engendered thermal regulation. For such thin systems, the mean surface temperature and the outlet temperature—consequently, the heat extracted by the flowing fluid (coolant)—are invariant under flow reversal (i.e. swapping the inlet and outlet). Despite markedly different temperature fields under flow reversal, our newfound invariance—a discovery—holds for anisotropic thermal conductivity, any inlet and ambient temperatures, transient and steady-state responses, irregular domains, and arbitrary internal vascular topologies, including those with branching. The reported configuration-independent result benefits thermal regulation designers. For instance, the flexibility in the coolant’s inlet location eases coordination challenges between electronics and various delivery systems in microfluidic devices without compromising performance (e.g. soft implantable coolers for pain management). Last but not least, the invariance offers an innovative way to verify computer codes, especially when analytical solutions are unavailable for intricate domain and vascular configurations.
| S-EPMC10438884 | biostudies-literature
Project description:Given a graph
| S-EPMC7254919 | biostudies-literature
Project description:The betweenness centrality, a path-based global measure of flow, is a static predictor of congestion and load on networks. Here we demonstrate that its statistical distribution is invariant for planar networks, that are used to model many infrastructural and biological systems. Empirical analysis of street networks from 97 cities worldwide, along with simulations of random planar graph models, indicates the observed invariance to be a consequence of a bimodal regime consisting of an underlying tree structure for high betweenness nodes, and a low betweenness regime corresponding to loops providing local path alternatives. Furthermore, the high betweenness nodes display a non-trivial spatial clustering with increasing spatial correlation as a function of the edge-density. Our results suggest that the spatial distribution of betweenness is a more accurate discriminator than its statistics for comparing static congestion patterns and its evolution across cities as demonstrated by analyzing 200 years of street data for Paris.
| S-EPMC6021391 | biostudies-literature
Project description:A large body of structural work conducted over the past ten years has elucidated mechanistic details related to 3' to 5' processing and decay of RNA substrates by the RNA exosome. This chapter will focus on the structural organization of eukaryotic exosomes and their evolutionary cousins in bacteria and archaea with an emphasis on mechanistic details related to substrate recognition and to 3' to 5' phosphorolytic exoribonucleolytic activities of bacterial and archaeal exosomes as well as the hydrolytic exoribonucleolytic and endoribonucleolytic activities of eukaryotic exosomes. These points will be addressed in large part through presentation of crystal structures ofphosphorolytic enzymes such as bacterial RNase PH, PNPase and archaeal exosomes and crystal structures ofthe eukaryotic exosome and exosome sub-complexes in addition to standalone structures of proteins that catalyze activities associated with the eukaryotic RNA exosome, namely Rrp44, Rrp6 and their bacterial counterparts.
| S-EPMC3138715 | biostudies-literature
Project description:Molecular tunnels regulate delivery of substrates/intermediates in enzymes which either harbor deep-seated reaction centers or are for transport of reactive/toxic intermediates that need to be specifically delivered. Here, we focus on the importance of structural diversity in tunnel architectures, especially for the gaseous substrate translocation, in rendering differential substrate preferences and directionality. Two major types of tunnels have been discussed, one that transports stable gases from the environment to the active site, namely, external gaseous (EG) tunnels, and the other that transports molecules between active sites, namely, internal gaseous (IG) tunnels. Aspects as to how the gaseous tunnels have shaped during the course of evolution and their potential to modulate the substrate flow and enzymatic function are examined. In conclusion, the review highlights our perspective on the pulsation mechanism that could facilitate unidirectional translocation of the gaseous molecules through buried tunnels.
| S-EPMC8674909 | biostudies-literature
Project description:How phospholipids are trafficked between the bacterial inner and outer membranes through the hydrophilic space of the periplasm is not known. We report that members of the mammalian cell entry (MCE) protein family form hexameric assemblies with a central channel capable of mediating lipid transport. The E. coli MCE protein, MlaD, forms a ring associated with an ABC transporter complex in the inner membrane. A soluble lipid-binding protein, MlaC, ferries lipids between MlaD and an outer membrane protein complex. In contrast, EM structures of two other E. coli MCE proteins show that YebT forms an elongated tube consisting of seven stacked MCE rings, and PqiB adopts a syringe-like architecture. Both YebT and PqiB create channels of sufficient length to span the periplasmic space. This work reveals diverse architectures of highly conserved protein-based channels implicated in the transport of lipids between the membranes of bacteria and some eukaryotic organelles.
| S-EPMC5467742 | biostudies-literature
Project description:The integration of data from multiple global assays is essential to understanding dynamic spatiotemporal interactions within cells. In a companion paper, we reported a data integration methodology, designated Pointillist, that can handle multiple data types from technologies with different noise characteristics. Here we demonstrate its application to the integration of 18 data sets relating to galactose utilization in yeast. These data include global changes in mRNA and protein abundance, genome-wide protein-DNA interaction data, database information, and computational predictions of protein-DNA and protein-protein interactions. We divided the integration task to determine three network components: key system elements (genes and proteins), protein-protein interactions, and protein-DNA interactions. Results indicate that the reconstructed network efficiently focuses on and recapitulates the known biology of galactose utilization. It also provided new insights, some of which were verified experimentally. The methodology described here, addresses a critical need across all domains of molecular and cell biology, to effectively integrate large and disparate data sets.
| S-EPMC1297683 | biostudies-literature
Project description:We analysed the RNA-seq profile of larval and adult trachea of the fruitfly Drosophila melanogaster, as well as from whole flies.
2024-02-12 | GSE225000 | GEO
Project description:The control of gene expression is an important tool for metabolic engineering, the design of synthetic gene networks, and protein manufacturing. The most successful approaches to date are based on modulating mRNA synthesis via an inducible coupling to transcriptional effectors. Here we present a biological programming structure that leverages a system of engineered transcription factors and complementary genetic architectures. We use a modular design strategy to create 27 non-natural and non-synonymous transcription factors using the lactose repressor topology as a guide. To direct systems of engineered transcription factors we employ parallel and series genetic (DNA) architectures and confer fundamental and combinatorial logical control over gene expression. Here we achieve AND, OR, NOT, and NOR logical controls in addition to two non-canonical half-AND operations. The basic logical operations and corresponding parallel and series genetic architectures represent the building blocks for subsequent combinatorial programs, which display both digital and analog performance.
| S-EPMC6803630 | biostudies-literature