SceneNet: Understanding Real World Indoor Scenes With Synthetic Data

Scene understanding is a prerequisite to many high level tasks for any automated intelligent machine operating in real world environments. Recent attempts with supervised learning have shown promise in this direction but also highlighted the need for enormous quantity of supervised data --- performance increases in proportion to the amount of data used. However, this quickly becomes prohibitive when considering the manual labour needed to collect such data. In this work, we focus our attention on depth based semantic per-pixel labelling as a scene understanding problem and show the potential of computer graphics to generate virtually unlimited labelled data from synthetic 3D scenes. By carefully synthesizing training data with appropriate noise models we show comparable performance to state-of-the-art RGBD systems on NYUv2 dataset despite using only depth data as input and set a benchmark on depth-based segmentation on SUN RGB-D dataset. Additionally, we offer a route to generating synthesized frame or video data, and understanding of different factors influencing performance gains

SynthCam3D: Semantic Understanding With Synthetic Indoor Scenes

We are interested in automatic scene understanding from geometric cues. To this end, we aim to bring semantic segmentation in the loop of real-time reconstruction. Our semantic segmentation is built on a deep autoencoder stack trained exclusively on synthetic depth data generated from our novel 3D scene library, SynthCam3D. Importantly, our network is able to segment real world scenes without any noise modelling. We present encouraging preliminary results

Addressing the optimal silver content in bioactive glass systems in terms of BSA adsorption

Bioactive glasses doped with silver are aimed to minimize the risk of microbial contamination, and therefore, the influence of silver on the bioactive properties is an intense investigated task. However, the information related to the role played by silver, when added to the bioactive glass composition, on the biocompatibility properties is scarce. This aspect is essential as long as the silver content can influence the blood protein adsorption onto glass surface, affecting thus the material biocompatibility. Therefore, from the perspective of the biocompatibility standpoint, the finding of an optimal silver content in a bioactive glass is an extremely important issue. In this study, silver doped bioactive glasses were prepared by melt-derived technique, which eliminates the pores influence in the protein adsorption process. The obtained glasses were characterized by X-ray diffraction, UV-vis, X-ray Photoelectron (XPS) and Fourier Transform Infrared (FT-IR) spectroscopy, and afterwards they were investigated in terms of protein adsorption. Both UV-vis and XPS spectroscopy revealed the presence of Ag+ ions in all silver containing samples. By increasing the silver content, metallic Ag0 appears, the highest amount being observed for the sample with 1 mol% AgO2. Electron Paramagnetic Resonance measurements evidenced that the amount of spin labeled serum albumin attached on the surface increases with the silver content. The results obtained by analyzing the information derived from Atomic Force Microscopy and FT-IR measurements indicate that the occurrence of metallic Ag0 in the samples structure influences the secondary structure of the adsorbed protein. Based on the results derived from the protein response upon interaction with the investigated glass calcium-phosphate based system it was determined the optimal silver oxide concentration for which the secondary structure of the adsorbed protein is similar with that of the free one. This concentration was found to be 0.5 mol%

Preliminary archaeometric investigation on Middle Neolithic siliceous tools from Limba-Oarda de Jos (Transylvania, Romania)

The present archaeometric study focuses on a set of archaeological siliceous lithic tools that are assigned to the early Vinča culture period (Vinča A and Vinča B1). They were found in several pit-houses at Limba-Oarda de Jos (SW Transylvania, Romania), an open settlement that has been dated to 5,405-5,310 cal. BCE, a period in the Middle Neolithic. A total of 322 retouched tools and débitage pieces were typologically and macroscopically investigated. From these, 20 pieces were analyzed by polarized light optical microscopy (OM) and 10 pieces were analyzed by Fourier-transform infrared spectroscopy (FTIR) in order to identify compositional characteristics, define the petrographic type, and establish the spectral fingerprint of each material. Four petrographic types were discriminated: radiolarite, chert, fossiliferous chert, and siliceous limestone. Mineralogically, the tools primarily consist of a mass of microquartz and fibrous microquartz (called also ‘chalcedony’) associated with radiolarians remnants (in radiolarites); fossil shell fragments (in the fossiliferous chert); and limestone components, such as ooliths and pellets (in the siliceous limestone). All samples show distinct FTIR bands, most of which are assigned to microquartz, quartz, and fibrous microquartz. The deconvolution of the FTIR spectra in the 950-1300 cm-1 domain reveals the contribution of several other phases, such as calcite and clay minerals. The results support the assumption that the tools made of chert, fossiliferous chert, and siliceous limestone were produced at the site from nodules that probably originated from the Upper Jurassic chert-bearing limestone that crops out nearby in the Trascău Mts. The tools made of radiolarite were most likely brought to the site as finished products from the Trascău Mts

Perception Test: A Diagnostic Benchmark for Multimodal Video Models

We propose a novel multimodal video benchmark - the Perception Test - to evaluate the perception and reasoning skills of pre-trained multimodal models (e.g. Flamingo, BEiT-3, or GPT-4). Compared to existing benchmarks that focus on computational tasks (e.g. classification, detection or tracking), the Perception Test focuses on skills (Memory, Abstraction, Physics, Semantics) and types of reasoning (descriptive, explanatory, predictive, counterfactual) across video, audio, and text modalities, to provide a comprehensive and efficient evaluation tool. The benchmark probes pre-trained models for their transfer capabilities, in a zero-shot / few-shot or limited finetuning regime. For these purposes, the Perception Test introduces 11.6k real-world videos, 23s average length, designed to show perceptually interesting situations, filmed by around 100 participants worldwide. The videos are densely annotated with six types of labels (multiple-choice and grounded video question-answers, object and point tracks, temporal action and sound segments), enabling both language and non-language evaluations. The fine-tuning and validation splits of the benchmark are publicly available (CC-BY license), in addition to a challenge server with a held-out test split. Human baseline results compared to state-of-the-art video QA models show a significant gap in performance (91.4% vs 43.6%), suggesting that there is significant room for improvement in multimodal video understanding. Dataset, baselines code, and challenge server are available at https://github.com/deepmind/perception_testComment: 25 pages, 11 figure

Initial characterization, dosimetric benchmark and performance validation of Dynamic Wave Arc

Background: Dynamic Wave Arc (DWA) is a clinical approach designed to maximize the versatility of Vero SBRT system by synchronizing the gantry-ring noncoplanar movement with D-MLC optimization. The purpose of this study was to verify the delivery accuracy of DWA approach and to evaluate the potential dosimetric benefits. Methods: DWA is an extended form of VMAT with a continuous varying ring position. The main difference in the optimization modules of VMAT and DWA is during the angular spacing, where the DWA algorithm does not consider the gantry spacing, but only the Euclidian norm of the ring and gantry angle. A preclinical version of RayStation v4.6 (RaySearch Laboratories, Sweden) was used to create patient specific wave arc trajectories for 31 patients with various anatomical tumor regions (prostate, oligometatstatic cases, centrally-located non-small cell lung cancer (NSCLC) and locally advanced pancreatic cancer-LAPC). DWA was benchmarked against the current clinical approaches and coplanar VMAT. Each plan was evaluated with regards to dose distribution, modulation complexity (MCS), monitor units and treatment time efficiency. The delivery accuracy was evaluated using a 2D diode array that takes in consideration the multi-dimensionality of DWA during dose reconstruction. Results: In centrally-located NSCLC cases, DWA improved the low dose spillage with 20 %, while the target coverage was increased with 17 % compared to 3D CRT. The structures that significantly benefited from using DWA were proximal bronchus and esophagus, with the maximal dose being reduced by 17 % and 24 %, respectively. For prostate and LAPC, neither technique seemed clearly superior to the other; however, DWA reduced with more than 65 % of the delivery time over IMRT. A steeper dose gradient outside the target was observed for all treatment sites (p < 0.01) with DWA. Except the oligometastatic cases, where the DWA-MCSs indicate a higher modulation, both DWA and VMAT modalities provide plans of similar complexity. The average γ (3 % /3 mm) passing rate for DWA plans was 99.2 ± 1 % (range from 96.8 to 100 %). Conclusions: DWA proven to be a fully functional treatment technique, allowing additional flexibility in dose shaping, while preserving dosimetrically robust delivery and treatment times comparable with coplanar VMAT

Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials

The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based endpoint selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy, corticobasal syndrome, multiple system atrophy and related disorders, to compare candidate clinical trial endpoints. In this multicentre United Kingdom study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and magnetic resonance imaging assessments at baseline, six and twelve-months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, progressive supranuclear palsy-subcortical (progressive supranuclear palsy-parkinsonism and progressive gait freezing subtypes), progressive supranuclear palsy-cortical (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech-and-language, and progressive supranuclear palsy-corticobasal syndrome subtypes), multiple system atrophy-parkinsonism, multiple system atrophy-cerebellar, corticobasal syndrome with and without evidence of Alzheimer’s disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling, and sample sizes for clinical trials of disease modifying agents, according to group and assessment type. Two hundred forty-three people were recruited (117 progressive supranuclear palsy, 68 corticobasal syndrome, 42 multiple system atrophy and 16 indeterminate; 138 [56.8%] male; age at recruitment 68.7 ± 8.61 years). One hundred fifty-nine completed six-month assessment (82 progressive supranuclear palsy, 27 corticobasal syndrome, 40 multiple system atrophy and 10 indeterminate) and 153 completed twelve-month assessment (80 progressive supranuclear palsy, 29 corticobasal syndrome, 35 multiple system atrophy and 9 indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N &amp;lt; 100 required for one-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease specific. In conclusion, phenotypic variance within progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial endpoints, from potential functional, cognitive, clinical or neuroimaging measures of disease progression

Diagnosis Across the Spectrum of Progressive Supranuclear Palsy and Corticobasal Syndrome

IMPORTANCE: Patients with atypical parkinsonian syndromes (APS), including progressive supranuclear palsy (PSP), corticobasal syndrome (CBS) and multiple system atrophy (MSA), may be difficult to distinguish in early stages and are often misdiagnosed as Parkinson’s disease (PD). The diagnostic criteria for PSP have been updated to encompass a range of clinical subtypes, but have not been prospectively studied. OBJECTIVE: To define the distinguishing features of PSP and CBS, and to assess their usefulness in facilitating early diagnosis and separation from PD. DESIGN, SETTING, PARTICIPANTS: Cohort study which recruited APS and PD patients from movement disorder clinics across the UK from September 2015 to December 2018, and will follow up patients over 5 years. APS patients were stratified into PSP-Richardson syndrome, PSP-subcortical (including PSP-parkinsonism and PSP-progressive gait freezing cases), PSP-cortical (including PSP-frontal and PSP/CBS overlap cases), MSA-parkinsonism, MSA-cerebellar, CBS-Alzheimer’s and CBS-non-Alzheimer’s groups. MAIN OUTCOME MEASURES: Baseline group comparisons were conducted using: 1) Clinical trajectory; 2) Cognitive screening scales; 3) Serum neurofilament light chain (NF-L); 4) TRIM11, ApoE and MAPT genotypes; 5) Volumetric MRI. RESULTS: 222 APS cases (101 PSP, 55 MSA, 40 CBS and 26 indeterminate) were recruited (58% male; mean age at recruitment, 68.3 years). Age-matched controls (n=76) and PD cases (n=1967) were also included. Concordance between the ante-mortem clinical diagnosis and pathological diagnosis was achieved in 12/13 (92%) of PSP and CBS cases coming to post-mortem. Applying the MDS PSP diagnostic criteria almost doubled the number of patients diagnosed with PSP. 49/101 (49%) of reclassified PSP patients did not have classical PSP-Richardson syndrome. PSP-subcortical patients had a longer diagnostic latency and a more benign clinical trajectory than PSP-Richardson syndrome and PSP-cortical (p<0.05). PSP-subcortical was distinguished from PSP-cortical and PSP-Richardson syndrome by cortical volumetric MRI measures (AUC 0.84-0.89), cognitive profile (AUC 0.80-0.83), serum NF-L (AUC 0.75-0.83) and TRIM11 rs564309 genotype. Midbrain atrophy was a common feature of all PSP subtypes. 8/17 (47%) of CBS patients with CSF analysis were identified as having CBS-Alzheimer’s. CBS-Alzheimer’s patients had a longer diagnostic latency, relatively benign clinical trajectory, greater cognitive impairment and higher APOE-ε4 allele frequency than CBS-non-Alzheimer’s (p<0.05, AUC 0.80-0.87). Serum NF-L levels distinguished PD from PSP and CBS (p<0.05, AUC 0.80). CONCLUSIONS AND RELEVANCE: Clinical, therapeutic and epidemiological studies focusing on PSP-Richardson syndrome are likely to miss a large number of patients with underlying PSP-tau pathology. CSF analysis defines a distinct CBS-Alzheimer’s subgroup. PSP and CBS subtypes have distinct characteristics that may enhance their early diagnosis

Uganda's experience in Ebola virus disease outbreak preparedness, 2018-2019.

BACKGROUND: Since the declaration of the 10th Ebola Virus Disease (EVD) outbreak in DRC on 1st Aug 2018, several neighboring countries have been developing and implementing preparedness efforts to prevent EVD cross-border transmission to enable timely detection, investigation, and response in the event of a confirmed EVD outbreak in the country. We describe Uganda's experience in EVD preparedness. RESULTS: On 4 August 2018, the Uganda Ministry of Health (MoH) activated the Public Health Emergency Operations Centre (PHEOC) and the National Task Force (NTF) for public health emergencies to plan, guide, and coordinate EVD preparedness in the country. The NTF selected an Incident Management Team (IMT), constituting a National Rapid Response Team (NRRT) that supported activation of the District Task Forces (DTFs) and District Rapid Response Teams (DRRTs) that jointly assessed levels of preparedness in 30 designated high-risk districts representing category 1 (20 districts) and category 2 (10 districts). The MoH, with technical guidance from the World Health Organisation (WHO), led EVD preparedness activities and worked together with other ministries and partner organisations to enhance community-based surveillance systems, develop and disseminate risk communication messages, engage communities, reinforce EVD screening and infection prevention measures at Points of Entry (PoEs) and in high-risk health facilities, construct and equip EVD isolation and treatment units, and establish coordination and procurement mechanisms. CONCLUSION: As of 31 May 2019, there was no confirmed case of EVD as Uganda has continued to make significant and verifiable progress in EVD preparedness. There is a need to sustain these efforts, not only in EVD preparedness but also across the entire spectrum of a multi-hazard framework. These efforts strengthen country capacity and compel the country to avail resources for preparedness and management of incidents at the source while effectively cutting costs of using a "fire-fighting" approach during public health emergencies