Closing the Aboriginal Education Gap: A Systematic Review of Indigenous Educational Experiences in Canada

Indigenous learners represent a pool of untapped talents for positively influencing Canada’s economy. But there is a policy need to better enable indigenous learners’ access to higher education. This study presents a synthesis of views and perspectives extracted from eight published studies concerning Aboriginal educational experiences. Canadian indigenous learners were found to have the following views regarding their experiences with post-secondary education: anxiety about moving away from home, trepidation about transitioning from rural to urban spaces, uncertainty about social acceptance and long-term prospects; fear of racism and racial exclusion; and worry that their traditions will not be acknowledged or respected

Light and electron microscopical studies of the effect of cryosurgery on skeletal muscle and peripheral nerve of the guinea pig and horse skin

When living cells or tissues are reduced to very low temperatures cell and tissue destruction can occur. The controlled destruction of diseased tissue in clinical patients by the application of cold is termed - CRYOSURGERY - in which Kryos in ancient Greek means frost.Cryosurgery is a clinicEil technique applied to diseased animal tissues and particularly to malignant tumours. The diseased tissues are subjected to direct sub-zero temperatures. Following treatment the tissues necrose and are sloughed. The subsequent healing is by secondary intention. Cryosurgery is being used increasingly in human and veterinary practice and many questions remain to be answered about the destructive power of cryosurgery on living tissue and the fate of non-diseased tissue adjacent to a cryosurgical lesion.There is a considerable amount of recorded data concerning tissue damage, death and repair following several types of injury including the effect of freezing. This present study was designed to observe the effect of controlled freezing on living tissues to cryogenic or cryo-destructive temperatures, with particular reference to the healing processes involved and the degree of tissue repair in different areas of the cryo-lesion.Skeletal muscle and peripheral nerves are frequently frozen either intentionally or inadvertently, during cryo-therapy of deeper lesions and it was considered important to examine the effects of cold injury in these tissues.The investigation is related to the histopathology of the tissue changes during destruction, repair and regeneration employing light microscopy and electron microscopy techniques.Cryosurgery has been employed with success in the treatment of lesions of the skin and adnexa in man and some species of domestic animals but comparable results have not been achieved in treating benign fibrous skin tumours in the horse (Borthwick, 1970). There was a high percentage of recurrence of neoplasms in cryosurgically treated horse skin. The clinical problems of the surgery of horse skin stimulated the third part of the investigations reported in this thesis

Reasoning system for real time reactive systems

Real time reactive systems are complex systems that react with their environment through stimulus response behaviour. TROMLAB development environment is a formal system being developed at Concordia University. It is the basis of the real time reactive system that will be described in this thesis. One of the main uses of the simulation tool is debugging. The Reasoning System is a very good complement of the simulation tool. The scope of this thesis is the study of a Reasoning System that can be used along with the simulation tool to help debug the design and verify system properties during the development phase in TROMLAB environment

Micromechanical material models for polymer composites through advanced numerical simulation techniques

In order to reduce laboratory and experiments expenses, one would try to make predictions of a new material’s behavior and response by numerical simulations, with the chief goal being to speed up the trial and error experimental testing and to be able to simulate real phenomena that occur at the micro level of the composites that cannot be accurately implemented in the existing analytical models. The recent dramatic increase in computational power available for mathematical modeling and simulation raises the possibilities that modern numerical methods can play a significant role in the analysis of heterogeneous microstructures. This fact has motivated the work that will be presented in this work, which focuses on the methodology of building up an appropriate finite element material model describing the microstructure of the composite. It contains numerical homogenization practice and theory, as well as micro structural material modeling by using numerical simulation techniques on representative volume elements (RVEs). This work deals with the determination of macroscopic material properties of polymer composites by meso-mechanical numerical modeling. Focus is laid on the methodology how to build up appropriate representative volume elements (RVE) to describe the microstructure of spherical-particles and fibers reinforced composites and how to apply appropriate 3D boundary conditions. This work includes the comparison of the micro structural simulated FE-models with existing empirical and semi analytical formulations like Mori-Tanaka and the interpolative double inclusion (Lielens’ Model) that are used extensively in material modeling. Material characterization experiments are done on a particle reinforced polymer composite and its unfilled matrix to extract the material properties then compared with numerical homogenization applied on our micro material models. Various conclusions and results are discussed for the ‘know how’ in building the appropriate or preeminent representative material model based on the microstructure of the composite. 3D periodic and homogeneous boundary conditions are comprehensively studied, developed and applied to our RVEs. A new approach and technique is established for the 3D periodic boundary conditions. Different cases of numerical homogenization are examined, the isotropic case assumed for the particle filled composites (spherical inclusions) and the transverse isotropic/Orthotropic cases assumed for the fully-aligned/General-Orientation short-fiber reinforced composites (sphero-cylindrical and cylindrical inclusions)

Propose Two Methods To Find Values of The Aligned And Unaligned Inductance of The Switched Reluctance Motor

Aligned and unaligned inductances of SRM are needed for modeling and simulation program. Two simple methods have been suggested in this research to measure value of these inductances. It has been compared between two method depending on the shape of the motor current taken practically with the simulation current after compensating the value of the inductance in the simulation model and chose the most accurate method to measure the inductance. The values of the aligned and unaligned inductance in both methods in sequence are (101, 70, 74.5, 59.5). Through compensation the inductance values in the simulation model and compare the performance of this model with the practical performance, it was reached that the first test the nearest 93% of the practical value compared with the second test, which reaches matching ratio to 79%. The specification motor used was: type motor-SRM80L, Power rated=550watt, Number of phases=4, Number of poles 8 in stator and 4 in rotor, rated speed=1000rpm, rated torque=5N.m, rated current=4.5A, Driver AC=230v, Motor DC=285v

LIDAR-Based Lane Marking Detection For Vehicle Positioning in an HD Map

International audienceAccurate self-vehicle localization is an important task for autonomous driving and ADAS. Current GNSS-basedsolutions do not provide better than 2-3 m in open-sky environments. Moreover, map-based localization using HDmaps became an interesting source of information for intelligent vehicles. In this paper, a Map-based localization using a multi-layer LIDAR is proposed. Our method mainly relies on road lane markings and an HD map to achieve lane-level accuracy.At first, road points are segmented by analysing the geometric structure of each returned layer points. Secondly, thanks toLIDAR reflectivity data, road marking points are projected onto a 2D image and then detected using Hough Transform.Detected lane markings are then matched to our HD map using Particle Filter (PF) framework. Experiments are conducted on aHighway-like test track using GPS/INS with RTK correction as ground truth. Our method is capable of providing a lane-levellocalization with a 22 cm cross-track accuracy

LIDAR-Based road signs detection For Vehicle Localization in an HD Map

International audienceSelf-vehicle localization is one of the fundamental tasks for autonomous driving. Most of current techniques for global positioning are based on the use of GNSS (Global Navigation Satellite Systems). However, these solutions do not provide a localization accuracy that is better than 2-3 m in open sky environments [1]. Alternatively, the use of maps has been widely investigated for localization since maps can be pre-built very accurately. State of the art approaches often use dense maps or feature maps for localization. In this paper, we propose a road sign perception system for vehicle localization within a third party map. This is challenging since third party maps are usually provided with sparse geometric features which make the localization task more difficult in comparison to dense maps. The proposed approach extends the work in [2] where a localization system based on lane markings has been developed. Experiments have been conducted on a Highway-like test track using GNSS/INS with RTK corrections as ground truth (GT). Error evaluations are given as cross-track and along-track errors defined in the curvilinear coordinates [3] related to the map

LIDAR-Based High Reflective Landmarks (HRL)s For Vehicle Localization in an HD Map

International audienceAccurate localization is very important to ensure performance and safety of autonomous vehicles. In particular, with the appearance of High Definition (HD) sparse geometric road maps, many research works have been focusing on the deployment of accurate localization systems in a previously built map. In this paper, we solve a localization problem by matching road perceptions from a 3D LIDAR sensor with HD map elements. The perception system detects High Reflective Landmarks (HRL) such as: lane markings, road signs and guard rail reflectors (GRR) from a 3D point cloud. A particle filtering algorithm estimates the position of the vehicle by matching observed HRLs with HD map attributes. The proposed approach extends our work in [1] and [2] where a localization system based on lane markings and road signs has been developed. Experiments have been conducted on a highway-like test track using GNSS/INS with RTK corrections as a ground truth (GT). Error evaluations are given as cross-track (CT) and along-track (AT) errors defined in the curvilinear coordinates [3] related to the map. The obtained accuracies of our localization system is 18 cm for the cross-track error and 32 cm for the along-track error

Systematic review and meta-analysis of randomized clinical trials of anti-inflammatory agents in early-stage psychotic disorders

Background and Hypothesis: Accumulating evidence suggests that immune dysregulation is present in psychosis, however, evidence for anti-inflammatory treatments is mixed. This may be because studies need to focus on when inflammation offers a modifiable target. This review and meta-analysis sought to clarify the effects of anti-inflammatory agents from high-quality randomized trials in patients at clinical high risk for psychosis (CHR) and first-episode of psychosis (FEP). Study Design: Databases were searched until January 2025 for double-blind, randomized, placebo-controlled trials evaluating the effect of anti-inflammatory treatment compared with placebo in CHR and FEP populations. Primary outcomes were transition rates to psychosis in CHR and changes in total psychotic symptoms in FEP. Secondary outcomes included changes in symptoms in CHR and changes in symptom sub-scores in FEP. Study Results: Searches retrieved 2168 articles, with 17 meeting inclusion criteria (5 for CHR, 12 for FEP). In CHR, anti-inflammatory treatment was not associated with a significant reduction in transition to psychosis (odds ratio 0.88, 95% CI, 0.26-3.01, P = .80). In FEP, anti-inflammatory treatment demonstrated a significant reduction in total psychotic symptoms; (standardized mean differences = −0.38, 95% CI, −0.76 to 0.00, P = .05). Secondary outcomes showed no change in symptoms in CHR, and significant changes in Positive and Negative Syndrome Scale positive sub-scores in FEP. Conclusions: Adjuvant anti-inflammatory treatment may be efficacious in FEP. However, high heterogeneity was present across studies, with possible publication bias and small-study effects. We highlight the need for further, large, stage-specific trials to conclusively understand the potential therapeutic benefit of anti-inflammatory treatments in early psychosis