Lessons learned in the application of formal methods to the design of a storm surge barrier control system

The Maeslantkering is a key flood defense infrastructural system in the Netherlands. This movable barrier protects the city and harbor of Rotterdam, without impacting ship traffic under normal circumstances. Its control system, which operates completely autonomously, must be guaranteed to work correctly even under extreme weather conditions, although it closes only sporadically. During its development in the 1990's, the formal methods Z and Spin were used to increase reliability. As the availability of industrial expert knowledge on these formal methods declines, maintaining the specifications defined back then has become cumbersome. In the quest for an alternative mathematically rigorous approach, this paper reports on an experience in applying supervisory control synthesis. This formal method was recently applied successfully to other types of infrastructural systems like waterway locks, bridges, and tunnels, with the purpose to ensure safe behavior by coordinating hardware components. Here, we show that it can also be used to coordinate several (controller) software systems. Additionally, we compare the lessons learned from the originally used formal methods and link Z to supervisory control synthesis

Model Properties for Efficient Synthesis of Nonblocking Modular Supervisors

Supervisory control theory provides means to synthesize supervisors for systems with discrete-event behavior from models of the uncontrolled plant and of the control requirements. The applicability of supervisory control theory often fails due to a lack of scalability of the algorithms. We propose a format for the requirements and a method to ensure that the crucial properties of controllability and nonblockingness directly hold, thus avoiding the most computationally expensive parts of synthesis. The method consists of creating a control problem dependency graph and verifying whether it is acyclic. Vertices of the graph are modular plant components, and edges are derived from the requirements. In case of a cyclic graph, potential blocking issues can be localized, so that the original control problem can be reduced to only synthesizing supervisors for smaller partial control problems. The strength of the method is illustrated on two case studies: a production line and a roadway tunnel.Comment: Submitted to Journal of Control Engineering Practice, revision

Hispanic/Latinx ethnic differences in the relationships between behavioral inhibition, anxiety, and substance use in youth from the ABCD cohort

IntroductionElevated levels of behavioral inhibition (BI) may connote risk for both anxiety and substance use disorders. BI has consistently been shown to be associated with increased levels of anxiety, while the association between BI and substance use has been mixed. It is possible that the relationship between BI and substance use varies by individual difference factors. Hispanic/Latinx (H/L) youth in particular may have stronger relationships between BI, anxiety, and substance use.MethodsThe present study therefore evaluated (1) the prospective relationships between BI [assessed via self-reported behavioral inhibition system (BIS) scale scores], anxiety, and substance use in youth (n = 11,876) across baseline, 1-, and 2-year follow-ups of the Adolescent Brain Cognitive Development (ABCD) Study (ages 9–12) and (2) whether these relationships differed by H/L ethnicity while covarying for average behavioral approach system scores, race, sex, age, highest parental income, highest parental education, and past-year substance use (for analyses involving substance use outcomes).ResultsBaseline levels of BIS scores predicted increased anxiety symptoms at both 1- and 2-year follow-ups and did not differ by H/L ethnicity. Baseline levels of BIS scores also prospectively predicted increased likelihood of substance use at 2-year follow-up, but only for H/L youth and not at 1-year follow-up.DiscussionHigh scores on the BIS scale contribute risk to anxiety across ethnicities and may uniquely contribute to risk for substance use in H/L youth

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment