scholarly journals Critical Data Consolidation in MDM to Develop the Unified Version of Truth

2021 ◽  
Vol 12 (12) ◽  
Author(s):  
Dupinder Kaur ◽  
Dilbag Singh
Keyword(s):  
Critical Data ◽  
Data Consolidation

Tipi da commedia? Personaggi e trame nel Corpus Lysiacum

2015 ◽  
Vol 33 (2) ◽  
pp. 109-133
Author(s):  
Elena Colla
Keyword(s):  
Everyday Life ◽  
Critical Data ◽  
New Comedy

Modern scholars have sometimes noticed in the Lysianic speeches some affinities with characters and plots of the (New) Comedy. Through a survey of the corpus, this paper resumes the critical data, adds some new elements of similarity, not only with Comedy, but generally with literature and suggests that Lysias usually worked in this way. If so, it could be preferable to suppose that the logographer took the cue not from comedy, but from everyday life; secondarily, that he sketched characters and plots starting from the particular (his client) to the general; finally, that these artistic elements were useful to jury's persuasion and not added to a following publication.

Data Transfer from Clinic to Clinic – Queensland Perspective

OP-Journal ◽  
2021 ◽  
Author(s):  
Genevieve Westacott ◽  
Kirsten Vallmurr ◽  
Michael Schütz
Keyword(s):  
Information Exchange ◽  
Data Transfer ◽  
Data Communication ◽  
The State ◽  
Evolutionary Trend ◽  
Quality Healthcare ◽  
Digital Revolution ◽  
Critical Data ◽  
Secure Information ◽  
Security Standards

AbstractData transfer has been forced to evolve as digital technologies are implemented throughout various aspects of the healthcare system. Despite the uniqueness of both the geography and the population of Queensland, information exchange and data communication has continued to follow this evolutionary trend. There have been a number of different health reforms designed to integrate digital innovations and allow critical data and information to be shared with the appropriate health professionals when necessary. Strict healthcare legislation has been navigated and to provide newly upgraded technologies and processes while maintaining privacy, confidentiality and security standards. A large portion of the digital revolution has been the implementation of the national run project, the My Health Record and the state run project, the Integrated Electronic Medical Record. Both are platforms that allow secure information exchange allowing patients to have improved quality of care. To maintain the steady progress, both the state and federal governments have developed strategies and visions to help provide guidance and direct for ongoing and future digital projects. They also outline areas that require further advancements to ensure Queensland is delivering equitable, high quality healthcare.

scholarly journals Cardiac MRI and Myocardial Injury in COVID-19: Diagnosis, Risk Stratification and Prognosis

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 130
Author(s):  
Saagar K. Sanghvi ◽  
Logan S. Schwarzman ◽  
Noreen T. Nazir
Keyword(s):  
Risk Stratification ◽  
Myocardial Injury ◽  
Cardiac Tissue ◽  
Contractile Function ◽  
Imaging Modality ◽  
Acute Myocarditis ◽  
Myocardial Inflammation ◽  
Critical Data ◽  
Non Invasive ◽  
Risk Of Exposure

Myocardial injury is a common complication of the COVID-19 illness and is associated with a worsened prognosis. Systemic hyperinflammation seen in the advanced stage of COVID-19 likely contributes to myocardial injury. Cardiac magnetic resonance imaging (CMR) is the preferred imaging modality for non-invasive evaluation in acute myocarditis, enabling risk stratification and prognostication. Modified scanning protocols in the pandemic setting reduce risk of exposure while providing critical data regarding cardiac tissue inflammation and fibrosis, chamber remodeling, and contractile function. The growing use of CMR in clinical practice to assess myocardial injury will improve understanding of the acute and chronic sequelae of myocardial inflammation from various pathological etiologies.

scholarly journals Monitoring advances including consent: learning from COVID-19 trials and other trials running in UKCRC registered clinical trials units during the pandemic

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sharon B. Love ◽  
Emma Armstrong ◽  
Carrie Bayliss ◽  
Melanie Boulter ◽  
Lisa Fox ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Remote Monitoring ◽  
Research Collaboration ◽  
Monitoring Task ◽  
Critical Data ◽  
Site Monitoring ◽  
Clinical Trials Unit ◽  
Third Person ◽  
Trial Monitoring ◽  
The Uk

AbstractThe COVID-19 pandemic has affected how clinical trials are managed, both within existing portfolios and for the rapidly developed COVID-19 trials. Sponsors or delegated organisations responsible for monitoring trials have needed to consider and implement alternative ways of working due to the national infection risk necessitating restricted movement of staff and public, reduced clinical staff resource as research staff moved to clinical areas, and amended working arrangements for sponsor and sponsor delegates as staff moved to working from home.Organisations have often worked in isolation to fast track mitigations required for the conduct of clinical trials during the pandemic; this paper describes many of the learnings from a group of monitoring leads based in United Kingdom Clinical Research Collaboration (UKCRC) Clinical Trials Unit (CTUs) within the UK.The UKCRC Monitoring Task and Finish Group, comprising monitoring leads from 9 CTUs, met repeatedly to identify how COVID-19 had affected clinical trial monitoring. Informed consent is included as a specific issue within this paper, as review of completed consent documentation is often required within trial monitoring plans (TMPs). Monitoring is defined as involving on-site monitoring, central monitoring or/and remote monitoring.Monitoring, required to protect the safety of the patients and the integrity of the trial and ensure the protocol is followed, is often best done by a combination of central, remote and on-site monitoring. However, if on-site monitoring is not possible, workable solutions can be found using only central or central and remote monitoring. eConsent, consent by a third person, or via remote means is plausible. Minimising datasets to the critical data reduces workload for sites and CTU staff. Home working caused by COVID-19 has made electronic trial master files (TMFs) more inviting. Allowing sites to book and attend protocol training at a time convenient to them has been successful and worth pursuing for trials with many sites in the future.The arrival of COVID-19 in the UK has forced consideration of and changes to how clinical trials are conducted in relation to monitoring. Some developed practices will be useful in other pandemics and others should be incorporated into regular use.

scholarly journals An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds

2021 ◽  
Vol 13 (15) ◽  
pp. 3021
Author(s):  
Bufan Zhao ◽  
Xianghong Hua ◽  
Kegen Yu ◽  
Xiaoxing He ◽  
Weixing Xue ◽  
...  
Keyword(s):  
Semantic Segmentation ◽  
Point Clouds ◽  
Intelligent Vehicles ◽  
Critical Data ◽  
Multi Scale ◽  
3D Point Clouds ◽  
Cluster Optimization ◽  
Urban Scene ◽  
Processing Steps

Urban object segmentation and classification tasks are critical data processing steps in scene understanding, intelligent vehicles and 3D high-precision maps. Semantic segmentation of 3D point clouds is the foundational step in object recognition. To identify the intersecting objects and improve the accuracy of classification, this paper proposes a segment-based classification method for 3D point clouds. This method firstly divides points into multi-scale supervoxels and groups them by proposed inverse node graph (IN-Graph) construction, which does not need to define prior information about the node, it divides supervoxels by judging the connection state of edges between them. This method reaches minimum global energy by graph cutting, obtains the structural segments as completely as possible, and retains boundaries at the same time. Then, the random forest classifier is utilized for supervised classification. To deal with the mislabeling of scattered fragments, higher-order CRF with small-label cluster optimization is proposed to refine the classification results. Experiments were carried out on mobile laser scan (MLS) point dataset and terrestrial laser scan (TLS) points dataset, and the results show that overall accuracies of 97.57% and 96.39% were obtained in the two datasets. The boundaries of objects were retained well, and the method achieved a good result in the classification of cars and motorcycles. More experimental analyses have verified the advantages of the proposed method and proved the practicability and versatility of the method.

Coherent noise in marine seismic data

Geophysics ◽  
1983 ◽  
Vol 48 (7) ◽  
pp. 854-886 ◽  
Author(s):  
Ken Larner ◽  
Ron Chambers ◽  
Mai Yang ◽  
Walt Lynn ◽  
Willon Wai
Keyword(s):  
Seismic Data ◽  
Noise Suppression ◽  
Seismic Source ◽  
Coherent Noise ◽  
Critical Data ◽  
Predictive Deconvolution ◽  
Scattered Energy ◽  
Marine Seismic ◽  
The Many ◽  
Water Bottom

Despite significant advances in marine streamer design, seismic data are often plagued by coherent noise having approximately linear moveout across stacked sections. With an understanding of the characteristics that distinguish such noise from signal, we can decide which noise‐suppression techniques to use and at what stages to apply them in acquisition and processing. Three general mechanisms that might produce such noise patterns on stacked sections are examined: direct and trapped waves that propagate outward from the seismic source, cable motion caused by the tugging action of the boat and tail buoy, and scattered energy from irregularities in the water bottom and sub‐bottom. Depending upon the mechanism, entirely different noise patterns can be observed on shot profiles and common‐midpoint (CMP) gathers; these patterns can be diagnostic of the dominant mechanism in a given set of data. Field data from Canada and Alaska suggest that the dominant noise is from waves scattered within the shallow sub‐buttom. This type of noise, while not obvious on the shot records, is actually enhanced by CMP stacking. Moreover, this noise is not confined to marine data; it can be as strong as surface wave noise on stacked land seismic data as well. Of the many processing tools available, moveout filtering is best for suppressing the noise while preserving signal. Since the scattered noise does not exhibit a linear moveout pattern on CMP‐sorted gathers, moveout filtering must be applied either to traces within shot records and common‐receiver gathers or to stacked traces. Our data example demonstrates that although it is more costly, moveout filtering of the unstacked data is particularly effective because it conditions the data for the critical data‐dependent processing steps of predictive deconvolution and velocity analysis.

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