Learning with multiple representations: An example of a revision lesson in mechanics

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.Comment: 10 pages, 5 figures, 2 tables http://iopscience.iop.org/0031-912

SynTable: A Synthetic Data Generation Pipeline for Unseen Object Amodal Instance Segmentation of Cluttered Tabletop Scenes

In this work, we present SynTable, a unified and flexible Python-based dataset generator built using NVIDIA's Isaac Sim Replicator Composer for generating high-quality synthetic datasets for unseen object amodal instance segmentation of cluttered tabletop scenes. Our dataset generation tool can render a complex 3D scene containing object meshes, materials, textures, lighting, and backgrounds. Metadata, such as modal and amodal instance segmentation masks, occlusion masks, depth maps, bounding boxes, and material properties, can be generated to automatically annotate the scene according to the users' requirements. Our tool eliminates the need for manual labeling in the dataset generation process while ensuring the quality and accuracy of the dataset. In this work, we discuss our design goals, framework architecture, and the performance of our tool. We demonstrate the use of a sample dataset generated using SynTable by ray tracing for training a state-of-the-art model, UOAIS-Net. The results show significantly improved performance in Sim-to-Real transfer when evaluated on the OSD-Amodal dataset. We offer this tool as an open-source, easy-to-use, photorealistic dataset generator for advancing research in deep learning and synthetic data generation.Comment: Version

Emergency medical services key performance measurement in Asian cities

10.1186/s12245-015-0062-7International Journal of Emergency Medicine8

Dispatcher-assisted cardiopulmonary resuscitation for paediatric out-of-hospital cardiac arrest

Aim To evaluate communication issues during dispatcher-assisted cardiopulmonary resuscitation (DACPR) for paediatric out-of-hospital cardiac arrest in a structured manner to facilitate recommendations for training improvement. Methods A retrospective observational study evaluated DACPR communication issues using the SACCIA ® Safe Communication typology (Sufficiency, Accuracy, Clarity, Contextualization, Interpersonal Adaptation). Telephone recordings of 31 cases were transcribed verbatim and analysed with respect to encoding, decoding and transactional communication issues. Results Sixty SACCIA communication issues were observed in the 31 cases, averaging 1.9 issues per case. A majority of the issues were related to sufficiency (35%) and accuracy (35%) of communication between dispatcher and caller. Situation specific guideline application was observed in CPR practice, (co)counting and methods of compressions. Conclusion This structured evaluation identified specific issues in paediatric DACPR communication. Our training recommendations focus on situation and language specific guideline application and moving beyond verbal communication by utilizing the smart phone’s functions. Prospective efforts are necessary to follow-up its translation into better paediatric DACPR outcomes

Knowledge of Signs and Symptoms of Heart Attack and Stroke among Singapore Residents

Aim. To determine the level of knowledge of signs and symptoms of heart attack and stroke in Singapore resident population, in comparison to the global community. Methods. A population based, random sample of 7,840 household addresses was selected from a validated national sampling frame. Each participant was asked eight questions on signs and symptoms of heart attack and 10 questions on stroke. Results. The response rate was 65.2% with 4,192 respondents. The level of knowledge for preselected, common signs and symptoms of heart attack and stroke was 57.8% and 57.1%, respectively. The respondents scored a mean of 5.0 (SD 2.4) out of 8 for heart attack, while they scored a mean of 6.8 (SD 2.9) out of 10 for stroke. Respondents who were ≥50 years, with lower educational level, and unemployed/retired had the least knowledge about both conditions. The level of knowledge of signs and symptoms of heart attack and stroke in Singapore is comparable to USA and Canada. Conclusion. We found a comparable knowledge of stroke and heart attack signs and symptoms in the community to countries within the same economic, educational, and healthcare strata. However older persons, those with lower educational level and those who are unemployed/retired, require more public health education efforts

Impact of cardiac arrest centers on the survival of patients with nontraumatic out‐of‐hospital cardiac arrest : a systematic review and meta‐analysis

Background The role of cardiac arrest centers (CACs) in out‐of‐hospital cardiac arrest care systems is continuously evolving. Interpretation of existing literature is limited by heterogeneity in CAC characteristics and types of patients transported to CACs. This study assesses the impact of CACs on survival in out‐of‐hospital cardiac arrest according to varying definitions of CAC and prespecified subgroups. Methods and Results Electronic databases were searched from inception to March 9, 2021 for relevant studies. Centers were considered CACs if self‐declared by study authors and capable of relevant interventions. Main outcomes were survival and neurologically favorable survival at hospital discharge or 30 days. Meta‐analyses were performed for adjusted odds ratio (aOR) and crude odds ratios. Thirty‐six studies were analyzed. Survival with favorable neurological outcome significantly improved with treatment at CACs (aOR, 1.85 [95% CI, 1.52–2.26]), even when including high‐volume centers (aOR, 1.50 [95% CI, 1.18–1.91]) or including improved‐care centers (aOR, 2.13 [95% CI, 1.75–2.59]) as CACs. Survival significantly increased with treatment at CACs (aOR, 1.92 [95% CI, 1.59–2.32]), even when including high‐volume centers (aOR, 1.74 [95% CI, 1.38–2.18]) or when including improved‐care centers (aOR, 1.97 [95% CI, 1.71–2.26]) as CACs. The treatment effect was more pronounced among patients with shockable rhythm ( P =0.006) and without prehospital return of spontaneous circulation ( P =0.005). Conclusions were robust to sensitivity analyses, with no publication bias detected. Conclusions Care at CACs was associated with improved survival and neurological outcomes for patients with nontraumatic out‐of‐hospital cardiac arrest regardless of varying CAC definitions. Patients with shockable rhythms and those without prehospital return of spontaneous circulation benefited more from CACs. Evidence for bypassing hospitals or interhospital transfer remains inconclusive

The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile

<p>Abstract</p> <p>Background</p> <p>Overall gastric cancer survival remains poor mainly because there are no reliable methods for identifying highly curable early stage disease. Multi-protein profiling of gastric fluids, obtained from the anatomic site of pathology, could reveal diagnostic proteomic fingerprints.</p> <p>Methods</p> <p>Protein profiles were generated from gastric fluid samples of 19 gastric cancer and 36 benign gastritides patients undergoing elective, clinically-indicated gastroscopy using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on multiple ProteinChip arrays. Proteomic features were compared by significance analysis of microarray algorithm and two-way hierarchical clustering. A second blinded sample set (24 gastric cancers and 29 clinically benign gastritides) was used for validation.</p> <p>Results</p> <p>By significance analysyis of microarray, 60 proteomic features were up-regulated and 46 were down-regulated in gastric cancer samples (<it>p </it>< 0.01). Multimarker clustering showed two distinctive proteomic profiles independent of age and ethnicity. Eighteen of 19 cancer samples clustered together (sensitivity 95%) while 27/36 of non-cancer samples clustered in a second group. Nine non-cancer samples that clustered with cancer samples included 5 pre-malignant lesions (1 adenomatous polyp and 4 intestinal metaplasia). Validation using a second sample set showed the sensitivity and specificity to be 88% and 93%, respectively. Positive predictive value of the combined data was 0.80. Selected peptide sequencing identified pepsinogen C and pepsin A activation peptide as significantly down-regulated and alpha-defensin as significantly up-regulated.</p> <p>Conclusion</p> <p>This simple and reproducible multimarker proteomic assay could supplement clinical gastroscopic evaluation of symptomatic patients to enhance diagnostic accuracy for gastric cancer and pre-malignant lesions.</p