Novas técnicas para mapeamento geológico em planejamento de lavra a céu aberto com sensores aerotransportados

O planejamento de lavra depende diretamente de um processo eficiente e preciso de controle de teores e mapeamento de contatos entre litologias nas frentes de operação. Identificadas pelo processo de mapeamento geológico, as classes podem ser definidas por agrupamentos de materiais geológicos com base em seus atributos físicos, químicos e econômicos. Quanto mais acurado for o modelo, maior é o controle do planejamento sobre aspectos como diluição, recuperação, volumetria e consequentemente a assertividade no processo de reconciliação de massas e teores. Tradicionalmente, o geólogo responsável pelo mapeamento constrói o modelo com base em observações de frente de lavra, mas limitado pelas dimensões do corpo humano e pelos riscos atrelados aos perigos em campo. Com o crescente desenvolvimento de tecnologias de automação, baseadas em inteligência artificial, a classificação litológica pode ser aperfeiçoada por meio de ferramentas de aprendizado de máquina para treinamento computacional supervisionado. Os dados são classificados por meio de comparação estatística contra as porções de treinamento, onde as classes são previamente fornecidas por um profissional experiente e tomadas como verdadeiras. A partir de imagens adquiridas por veículos aéreos não tripulados de baixo custo, é feito um processamento fotogramétrico, o qual resulta em uma nuvem densa de pontos. Cada ponto apresenta, além das coordenadas cartesianas, as respectivas componentes de reflectância. Estes dados servem como porções de treinamento e validação de modelos de classificação automática. Por meio de algoritmos de aprendizado de máquina aplicados em nuvens de pontos, foi determinado que é possível criar um modelo de classificação automática de litologia em frentes de lavra de minas a céu aberto. Como aplicação prática, os parâmetros de lavra podem ser refinados em uma reconciliação proativa.Mining planning depends directly on an efficient and accurate process of grade control and mapping of contacts between lithologies on a mining face. Identified through geological mapping procedures, the classes might be defined by the grouping of geological materials, based on their physical, chemical and economical attributes. The more accurate is the model, the higher is the mine planning control on technical aspects, such as dilution, recovery, volume measurement and consequent assertiveness for the process of tonnes and grades reconciliation. Traditionally, the geologist responsible for mapping builds the model using observation data from the mining face, but limited by human body physical dimensions and by the risks associated to the field exposition. With the increase in automation technologies, based on artificial intelligence, lithological classification can benefit through the use of machine learning tools applied with supervised computational training. The data are classified by statistical comparison against training portions, onto which the classes are previously provided by an experienced professional and taken as real. Using images acquired by low cost unmanned aerial vehicles, a photogrammetric processing is performed, resulting on a dense point cloud. Each point presents the cartesian location coordinates and the respective reflectance components. These data are taken as training and validating portions for the automatic classification models. Using machine learning algorithms applied on point cloud information, it was determined that it is possible to create an automatic lithological classification model on open pit mining face. For practical planning application, the mining parameters may be refined as a proactive reconciliation

REST selectively represses a subset of RE1-containing neuronal genes in mouse embryonic stem cells.

REST is a transcriptional repressor that targets a group of neuronal genes in non-neuronal cells. In embryonic stem (ES) cells, REST has been implicated in controlling the expression of transcription factor genes that are crucial for lineage determination and for maintaining ES cell potential. Here, we asked whether REST directly regulates neural-specifying genes in mouse ES cells using siRNA-mediated REST knockdown and ES cells that lack functional REST protein as a result of gene targeting. Loss of REST did not affect the expression of any of ten transcription factor genes known to promote neural commitment and did not affect the expression of several microRNAs, including miR-21, a putative REST target in ES cells. REST-deficient ES cells retained the ability to self-renew and to undergo appropriate differentiation towards mesoderm, endoderm and ectoderm lineages upon LIF withdrawal. Genome-wide expression profiling showed that genes that were deregulated in the absence of REST were preferentially expressed in the brain and highly enriched for the presence of canonical REST binding sites (RE1). Chromatin immunoprecipitation studies confirmed these genes as direct targets of REST in ES cells. Collectively, these data show that REST selectively silences a cohort of neuronal genes in ES cells

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection