Description:
Free-standing magnetic field energy harvesters (FSMFEHs) have promising potential in charging sensors used in electrical power grids. The output power of the FSMFEH is highly dependent on the load resistance. However, the load resistance of the sensors varies over a wide range during the operation process. Therefore, a crucial challenge for an FSMFEH system is to maintain high output power over a wide load range. In this letter, an innovative reconfigurable rectifier-based FSMFEH system with two coils connected in parallel is proposed. First, a new structure of two identical coils in parallel is proposed in magnetic energy harvesting applications. Then, a reconfigurable rectifier with two operation modes is developed to incorporate the new coil structure. By switching between the full-bridge mode and the half-bridge mode according to the actual load demand, the proposed FSMFEH can maintain high output power over a wide load range. In addition, the mode transition can be easily achieved by shorting one of the diodes, leading to a simple and low-loss control. The effectiveness of the proposed FSMFEH system is verified based on a laboratory prototype. It is provided that the experimental result is consistent with the theoretical analysis. The output power can be maintained above 8.19 mW within the 50-1500
Description:
Research in texture feature approximation is still in the embryonic stage because of difficulties in developing a sound theoretical model to express the unique pattern in the intensity-variation of pixels in the neighbourhood of the pixel-of-interest so that it can sufficiently discriminate different textures. Local texture descriptors are widely used in image segmentation as they comprise pixel-wise features. The Weber local descriptor (WLD) with differential excitation and gradient orientation components, inspired by Weber's Law, has been leveraged in the state-of-the-art iterative contraction and merging (ICM) image segmentation technique. However, WLD has inherent drawbacks in the formulation of the components that limit its discriminatory capability. This paper introduces a novel texture descriptor by directly modelling the distribution of intensity-variation in the parametric space of the Weibull distribution using its shape and scale parameters. A unified 'joint scale' texture property is introduced, which can discriminate textures better than the individual parameters while keeping the length of the descriptor shorter. Additionally, the accuracy of WLD's gradient orientation component is improved by using an extended Sobel operator and expressing gradients in -
Description:
Autism spectrum conditions are a group of neurodevelopmental conditions that carries an array of co-occurring diagnoses, including a heightened risk of suicide attempts and suicide. This scoping review examined primary research focusing on autism and suicidality, to understand what is currently known on the topic, including how autism changes the presentation of suicidal thoughts and behavior and to assess the suicide awareness and prevention education programs currently available for autistic people, their families, and health professionals and support workers. A comprehensive search (November 2021) across Scopus, PubMed and CINAHL identified 39 articles from 38 studies. Three themes emerged, with five subthemes. 1. The prevalence of suicidality in autistic people 2. The presentation of suicidality in autistic people, including (a) risk of suicidality (b) gender, age, employment and education (c) co-occurring psychiatric conditions (d) autism traits and social communication (e) intellectual disability and 3. Autism-specific approaches to suicidal thoughts, behavior and prevention. Findings were mixed, including conflicting evidence on the risk of autism and suicidality, and limited evidence of resources related to autism-specific suicide awareness or information, and education or prevention programs.
Description:
Multiple sclerosis (MS) is a chronic autoimmune disease characterized by inflammation, demyelination of axons, and oligodendrocyte loss in the central nervous system. This leads to neurological dysfunction, including hand impairment, which is prevalent among patients with MS. However, hand impairment is the least targeted area for neurorehabilitation studies. Therefore, this study proposes a novel approach to improve hand functions compared to current strategies. Studies have shown that learning new skills in the motor cortex (M1) can trigger the production of oligodendrocytes and myelin, which is a critical mechanism for neuroplasticity. Transcranial direct current stimulation (tDCS) has been used to enhance motor learning and function in human subjects. However, tDCS induces non-specific effects, and concurrent behavioral training has been found to optimize its benefits. Recent research indicates that applying tDCS during motor learning can have priming effects on the long-term potentiation mechanism and prolong the effects of motor training in health and disease. Therefore, this study aims to assess whether applying repeated tDCS during the learning of a new motor skill in M1 can be more effective in improving hand functions in patients with MS than current neurorehabilitation strategies. If this approach proves successful in improving hand functions in patients with MS, it could be adopted as a new approach to restore hand functions. Additionally, if the application of tDCS demonstrates an accumulative effect in improving hand functions in patients with MS, it could provide an adjunct intervention during rehabilitation for these patients. This study will contribute to the growing body of literature on the use of tDCS in neurorehabilitation and could have a significant impact on the quality of life of patients with MS. 2023 Zoghi and Jaberzadeh.
Description:
Multiple sclerosis (MS) is a chronic autoimmune disease characterized by inflammation, demyelination of axons, and oligodendrocyte loss in the central nervous system. This leads to neurological dysfunction, including hand impairment, which is prevalent among patients with MS. However, hand impairment is the least targeted area for neurorehabilitation studies. Therefore, this study proposes a novel approach to improve hand functions compared to current strategies. Studies have shown that learning new skills in the motor cortex (M1) can trigger the production of oligodendrocytes and myelin, which is a critical mechanism for neuroplasticity. Transcranial direct current stimulation (tDCS) has been used to enhance motor learning and function in human subjects. However, tDCS induces non-specific effects, and concurrent behavioral training has been found to optimize its benefits. Recent research indicates that applying tDCS during motor learning can have priming effects on the long-term potentiation mechanism and prolong the effects of motor training in health and disease. Therefore, this study aims to assess whether applying repeated tDCS during the learning of a new motor skill in M1 can be more effective in improving hand functions in patients with MS than current neurorehabilitation strategies. If this approach proves successful in improving hand functions in patients with MS, it could be adopted as a new approach to restore hand functions. Additionally, if the application of tDCS demonstrates an accumulative effect in improving hand functions in patients with MS, it could provide an adjunct intervention during rehabilitation for these patients. This study will contribute to the growing body of literature on the use of tDCS in neurorehabilitation and could have a significant impact on the quality of life of patients with MS. 2023 Zoghi and Jaberzadeh.
Description:
Rock strength is a crucial factor to consider when designing and constructing underground projects. This study utilizes a gene expression programming (GEP) algorithm-based model to predict the true triaxial strength of rocks, taking into account the influence of rock genesis on their mechanical behavior during the model building process. A true triaxial strength criterion based on the GEP model for igneous, metamorphic and magmatic rocks was obtained by training the model using collected data. Compared to the modified Weibols-Cook criterion, the modified Mohr-Coulomb criterion, and the modified Lade criterion, the strength criterion based on the GEP model exhibits superior prediction accuracy performance. The strength criterion based on the GEP model has better performance in R2, RMSE and MAPE for the data set used in this study. Furthermore, the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different types. Compared to the existing strength criterion based on the genetic programming (GP) model, the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength (
Description:
Rock strength is a crucial factor to consider when designing and constructing underground projects. This study utilizes a gene expression programming (GEP) algorithm-based model to predict the true triaxial strength of rocks, taking into account the influence of rock genesis on their mechanical behavior during the model building process. A true triaxial strength criterion based on the GEP model for igneous, metamorphic and magmatic rocks was obtained by training the model using collected data. Compared to the modified Weibols-Cook criterion, the modified Mohr-Coulomb criterion, and the modified Lade criterion, the strength criterion based on the GEP model exhibits superior prediction accuracy performance. The strength criterion based on the GEP model has better performance in R2, RMSE and MAPE for the data set used in this study. Furthermore, the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different types. Compared to the existing strength criterion based on the genetic programming (GP) model, the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength (