2,582 research outputs found
Systematic investigation of trench filling with photo materials
Author Amal Dev Raj VilayilMasterarbeit Universität Linz 2022Arbeit auf den öffentlichen PCs in den Bibliotheken der JKU+Medizin abrufba
Clinical phenotyping and neuropathological correlates of neuromuscular disease
Peripheral neuropathies have a significant population prevalence which is likely to increase in the future. They can impose a significant burden on the quality of life. The use of nerve biopsy is an important diagnostic tool in the assessment of patients with neuropathies. Newer techniques have emerged; reducing the reliance on nerve biopsies to assist with diagnosis. Nonetheless, the information obtained from histopathology may still help to distinguish clinical phenotypes which in turn can potentially modify the clinical management of patients. However, no clear guidelines currently exist to assist clinicians considering nerve biopsies for their patients. During this Master’s project, a comprehensive database was created based on the analysis of clinical and pathological information derived from the medical records of patients who were referred for nerve biopsy. This neuromuscular database was analysed to study the diagnostic utility of nerve biopsies in the clinical workup of selected types of neuropathies. Patients with suspected vasculitic neuropathy were studied to determine the clinical parameters that influenced the presence of neuropathological findings supportive of a diagnosis of vasculitic neuropathy. Stepwise clinical progression, the presence of both sensory and motor features, and asymmetric or multifocal presentation best differentiated systemic and non-systemic vasculitic neuropathy from other conditions. Additionally, parameters that best differentiated systemic vasculitic neuropathy from other conditions included the presence of selected autoantibodies and elevated inflammatory markers. Nerve conduction studies (NCS) in patients with pathologically confirmed vasculitic neuropathy frequently demonstrated a pure axonal neuropathy with sensorimotor abnormalities. In contrast, a diagnostic exclusion of vasculitis was highest in patients with normal NCS, patients with upper limb dominant symptoms, and in patients with cerebrospinal fluid (CSF) pleocytosis or CSF protein above 110mg/dL. Nerve biopsies in patients with symptoms that were purely sensory or chronic and symmetric as well as patients with dominant demyelinating features on NCS were unlikely to demonstrate evidence of vasculitis. Patients with suspected paraproteinaemic neuropathy were studied to determine the clinical parameters that influenced the presence of neuropathological findings supportive of a diagnosis of paraproteinaemic neuropathy. The presence of an IgM paraprotein and absence of an IgG paraprotein best differentiated biopsy findings consistent with paraproteinaemic neuropathy from other diagnoses. Patients with an eventual clinical diagnosis of paraproteinaemic neuropathy were studied separately and it was determined that regardless of whether the nerve biopsy report suggested a diagnosis of paraproteinaemic neuropathy, there was no difference in the prevalence of changes to the management plan or to clinical outcomes. Overall, this thesis has established that in a cohort of patients referred for nerve biopsy, several clinical parameters influenced the pathological outcomes of nerve biopsy. Consequently, decision aids were created for clinicians to assist in deciding whether a referral for nerve biopsy was appropriate
Corrigendum to Programmed cell death in the lithium pilocarpine model: Evidence for NMDA receptor and ceramide-mediated mechanisms [Brain Dev 30 (2008) 513-519] (DOI:10.1016-j.braindev.2008.01.002)
[No abstract available]Mikati MA, 2008, BRAIN DEV-JPN, V30, P513, DOI 10.1016-j.braindev.2008.01.0020
open-AIMS/ADRIA.jl: v0.7.0-dev.1
What's Changed
Update use of functions due to new import approach by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/334
Migrate from SnoopPrecompile to PrecompileTools by @timholy in https://github.com/open-AIMS/ADRIA.jl/pull/335
Add planning horizon factor by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/336
Replace use of area attribute/field with call to function site_area() to ensure correct values by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/337
Remove reference to defunct fields when making factors constant by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/338
Make use of planning horizon in sims by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/340
Changes to support running ADRIA with external model (ReefMod Engine) data by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/341
CompatHelper: add new compat entry for SimpleWeightedGraphs at version 1, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/343
CompatHelper: add new compat entry for OrderedCollections at version 1, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/344
CompatHelper: bump compat for StatsBase to 0.34, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/345
Split ADRIA-mod domain definition by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/346
Add GBR zones by priority by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/347
Exit with error if given path is not a directory by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/350
Make Aviz into an extension package by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/349
CompatHelper: add new compat entry for Reexport at version 1, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/351
CompatHelper: add new compat entry for ImageMagick at version 1, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/352
Update bleaching mortality model to align with published paper by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/354
Add option to use JMcDM functions in ADRIA site selection by @Rosejoycrocker in https://github.com/open-AIMS/ADRIA.jl/pull/348
Address mismatched number of elements under certain conditions by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/358
Remove Copras method due to erroring by @Rosejoycrocker in https://github.com/open-AIMS/ADRIA.jl/pull/359
CompatHelper: bump compat for HypothesisTests to 0.11, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/363
CompatHelper: add new compat entry for JMcDM at version 0.7, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/362
Update documentation by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/361
Scenario discovery docs by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/364
Fix: Metric errors when applied to a single simulation by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/365
Address ranking errors in mcda outputs by @Rosejoycrocker in https://github.com/open-AIMS/ADRIA.jl/pull/367
Add temporal clustering by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/370
Fix incorrect type check by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/371
CompatHelper: add new compat entry for Clustering at version 0.15, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/372
CompatHelper: bump compat for Zarr to 0.9, (keep existing compat) by @github-actions in https://github.com/open-AIMS/ADRIA.jl/pull/373
Update time series clustering and add visualization functionality by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/374
Update scenario viz by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/355
Refactor run_scenarios to improve when running multiple rcps by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/376
Bump version number and add new author by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/378
Update docstrings for growth function by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/375
Add map visualization - displays k-area by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/356
Consider near-term conditions with greater weight than far-future conditions by @ConnectedSystems in https://github.com/open-AIMS/ADRIA.jl/pull/387
Changes to number of species in ADRIA by @Rosejoycrocker in https://github.com/open-AIMS/ADRIA.jl/pull/380
Temporal clustering for spatial data by @Zapiano in https://github.com/open-AIMS/ADRIA.jl/pull/382
New Contributors
@timholy made their first contribution in https://github.com/open-AIMS/ADRIA.jl/pull/335
@Zapiano made their first contribution in https://github.com/open-AIMS/ADRIA.jl/pull/370
Full Changelog: https://github.com/open-AIMS/ADRIA.jl/compare/v0.5.0...v0.7.0-dev.
The Cryosphere Discussions
www.geosci-model-dev-discuss.net/6/3003/2013/ doi:10.5194/gmdd-6-3003-2013 © Author(s) 2013. CC Attribution 3.0 License
System Safety in Healthcare: The Right and Wrong Ways to Perform Failure Mode and Effects Analysis (FMEA)
The objective of performing Failure Mode and Effects Analysis (FMEA) is to use sound risk management principles, coupled with innovative solutions that can assure high return on investment (ROI). Quality Guru Philip Crosby wrote in his book, Quality is Free, that quality is free if you do the right things at the right time. Essentially, the savings from avoiding fixes, process changes and lawsuits are much higher than the cost of doing things right. The principles of sound risk management, experienced by this paper’s co-author Dev Raheja as an international engineering management consultant over 30 years, include:
Identifying risks
Assessing risks
Mitigating risks
Orchestrating risk management
Aiming at high ROI without compromising safet
A role for SUMO modification in transcriptional repression and activation
Since the discovery of the SUMO (small ubiquitin-related modifier) family of proteins just over a decade ago, a plethora of substrates have been uncovered including many regulators of transcription. Conjugation of SUMO to target proteins has generally been considered as a repressive modification. However, there are now a growing number of examples where SUMOylation has been shown to activate transcription. Here, we discuss whether there is something intrinsically repressive about SUMOylation, or if the outcome of this modification in the context of transcription will prove to be largely substrate-dependent. We highlight some of the technical challenges that will be faced by attempting to answer this question
ready4show: Author Literate Programs to Share Insights from Applying the Ready4 Framework
ready4show provides tools for authoring technical documentation, analysis reports and scientific summaries to showcase insights generated by open, modular mental health system models.
This release corrects citation information.Matthew Hamilton and Glen Wiesner (2022). ready4show: Author Literate Programs to Share Insights from Applying the Ready4 Framework. Version 0.0.0.9098. Zenodo. https://doi.org/10.5281/zenodo.564456
Using cross-model learnings for the Gram Vaani ASR Challenge 2022
In the diverse and multilingual land of India, Hindi is spoken as a first language by a majority of its population. Efforts are made to obtain data in terms of audio, transcriptions, dictionary, etc. to develop speech-technology applications in Hindi. Similarly, the Gram-Vaani ASR Challenge 2022 provides spontaneous telephone speech, with natural back-ground and regional variations in Hindi. The challenge provides: 100 hours of labeled train-set, 5 hours of labeled dev-set and 1000 hours of unlabeled data-set. For the 'Closed Challenge', we trained an End-to-End (E2E) Conformer model using speed perturbations, SpecAugment techniques and use VTLN to handle any unknown speaker groups in the blind evaluation set. On the dev-set, we achieved a 30.3% WER compared to the 34.8% WER by the Challenge E2E baseline. For the 'Self Supervised Closed Challenge', a semi-supervised learning approach is used. We generate pseudo-transcripts for the unlabeled data using a hybrid TDNN-3gram LM model and trained an E2E model. This is then used as a seed for retraining the E2E model with high confidence data. Cross-model learning and refining of the E2E model gave 25.3% WER on the dev-set compared to ∼33-35% WER by the Challenge baseline that use wav2vec models.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Multimedia Computin
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