Digital speckle pattern interferometry applied to a surface roughness study

Surface roughness determination is of great interest for many applications. Several methods can be found in the literature, but most of them rely on indirect evaluation of the information, such a s photographic techniques. We propose a method to measure surface roughness that takes advantage of digital speckle pattern interferometry for obtaining the data, and of digital image processing for evaluating it. After defining the problem, a theoretical description is presented, and finally it is compared with experimental results, showing good agreement

Digital speckle pattern interferometry applied to a surface roughness study

Surface roughness determination is of great interest for many applications. Several methods can be found in the literature, but most of them rely on indirect evaluation of the information, such a s photographic techniques. We propose a method to measure surface roughness that takes advantage of digital speckle pattern interferometry for obtaining the data, and of digital image processing for evaluating it. After defining the problem, a theoretical description is presented, and finally it is compared with experimental results, showing good agreement.Facultad de Ingenierí

Digital speckle pattern interferometry applied to a surface roughness study

Surface roughness determination is of great interest for many applications. Several methods can be found in the literature, but most of them rely on indirect evaluation of the information, such a s photographic techniques. We propose a method to measure surface roughness that takes advantage of digital speckle pattern interferometry for obtaining the data, and of digital image processing for evaluating it. After defining the problem, a theoretical description is presented, and finally it is compared with experimental results, showing good agreement.Facultad de Ingenierí

Digital speckle pattern interferometry applied to a surface roughness study

Surface roughness determination is of great interest for many applications. Several methods can be found in the literature, but most of them rely on indirect evaluation of the information, such a s photographic techniques. We propose a method to measure surface roughness that takes advantage of digital speckle pattern interferometry for obtaining the data, and of digital image processing for evaluating it. After defining the problem, a theoretical description is presented, and finally it is compared with experimental results, showing good agreement.Facultad de Ingenierí

Relevant HRH leadership during public health emergencies

Background: Inadequate leadership capacity compounds the world’s workforce lack of preparedness for outbreaks of all sizes, as illustrated by the COVID-19 pandemic. Traditional human resources for health (HRH) leadership has focused on determining the health workforce requirements, often failing to fully consider the unpredictability associated with issues such as public health emergencies (PHE). Main arguments: The current COVID-19 pandemic demonstrates that policy-making and relevant leadership have to be efective under conditions of ethical uncertainty and with inconclusive evidence. The forces at work in health labor markets (HLM) entail leadership that bridges across sectors and all levels of the health systems. Developing and applying leadership competencies must then be understood from a systemic as well as an individual perspective. To address the challenges described and to achieve universal health coverage (UHC) by 2030, countries need to develop efective HRH leaderships relevant to the complexity of HLM in the most diverse contexts, including acute surge events during PHE. In complex and rapidly changing contexts, such as PHE, leadership needs to be attentive, nimble, adaptive, action oriented, transformative, accountable and provided throughout the system, i.e., authentic, distributed and participatory. This type of leadership is particularly important, as it can contribute to complex organizational changes as required in surge events associated with PHE, even in in the absence of formal management plans, roles, and structures. To deal with the uncertainty it needs agile tools that may allow prompt human resources impact assessments. Conclusions: The complexity of PHE requires transformative, authentic, distributed and participatory leadership of HRH. The unpredictable aspects of the dynamics of the HLM during PHE require the need to rethink, adapt and operationalize appropriate tools, such as HRH impact assessment tools, to redirect workforce operations rapidly and with precision

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

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

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

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