Miracle-dz/UniFAR-FTUs huggingface dataset:
Defect Width Assessment Based on the Near-Field Magnetic Flux Leakage Method

Magnetic flux leakage (MFL) testing has been widely used as a non-destructive testing method for various materials. However, it is difficult to separate the influences of the defect geometrical parameters such as depth, width, and length on the received leakage signals. In this paper, a “near-field” MFL method is proposed to quantify defect widths. Both the finite element modelling (FEM) and experimental studies are carried out to investigate the performance of the proposed method. It is found that that the distance between two peaks of the “near-field” MFL is strongly related to the defect width and lift-off value, whereas it is slightly affected by the defect depth. Based on this phenomenon, a defect width assessment relying on the “near-field” MFL method is proposed. Results show that relative judging errors are less than 5%. In addition, the analytical expression of the “near-field” MFL is also developed.
Carbon coating on metal oxide materials for electrochemical energy storage

During the past decades, nano-structured metal oxide electrode materials have received growing attention due to their low development cost and high theoretical specific capacity, accordingly, quite a lot of metal oxide electrode materials are being used in electrochemical energy storage devices. However, the further development was limited by the relatively low electrical conductivity and the volume expansion during electrochemical reactions. Thus, many approaches have been proposed to obtain high-efficiency metal oxide electrode materials, such as designing nanomaterials with ideal morphology and high specific surface area, optimizing with carbon-based materials (such as graphene and glucose) to prepare nanocomposites, combining with conductive substrates to enhance the conductivity of electrodes, etc. Owning to the advantages of low cost and high chemical stability of carbon materials, core–shell structure formed by carbon-coated metal oxides is considered to be a promising solution to solve these problems. Therefore, this review mainly focuses on recent research advances in the field of carbon-coated metal oxides for energy storage, summarizing the advantages and disadvantages of common metal oxides and different types of carbon sources, and proposing methods to optimize the material properties in terms of structure and morphology, carbon layer thickness, coating method, specific surface area and pore size distribution, as well as improving electrical conductivity. In addition, the double or multi-layer coating strategy is also a reflection of the continuous development of carbon coating method. Hopefully, this rereview may provide a new direction for the renewal and development of future energy storage electrode materials.
Seasonal Snowpack Classification Based on Physical Properties Using Near-Infrared Proximal Hyperspectral Data

This paper proposes an innovative method for classifying the physical properties of the seasonal snowpack using near-infrared (NIR) hyperspectral imagery to discriminate the optical classes of snow at different degrees of metamorphosis. This imaging system leads to fast and non-invasive assessment of snow properties. Indeed, the spectral similarity of two samples indicates the similarity of their chemical composition and physical characteristics. This can be used to distinguish, without a priori recognition, between different classes of snow solely based on spectral information. A multivariate data analysis approach was used to validate this hypothesis. A principal component analysis (PCA) was first applied to the NIR spectral data to analyze field data distribution and to select the spectral range to be exploited in the classification. Next, an unsupervised classification was performed on the NIR spectral data to select the number of classes. Finally, a confusion matrix was calculated to evaluate the accuracy of the classification. The results allowed us to distinguish three snow classes of typical shape and size (weakly, moderately, and strongly metamorphosed snow). The evaluation of the proposed approach showed that it is possible to classify snow with a success rate of 85% and a kappa index of 0.75. This illustrates the potential of NIR hyperspectral imagery to distinguish between three snow classes with satisfactory success rates. This work will open new perspectives for the modelling of physical parameters of snow using spectral data.
Designing a Simple Fiducial Marker for Localization in Spatial Scenes Using Neural Networks

The paper describes the process of designing a simple fiducial marker. The marker is meant for use in augmented reality applications. Unlike other systems, it does not encode any information, but it can be used for obtaining the position, rotation, relative size, and projective transformation. Also, the system works well with motion blur and is resistant to the marker’s imperfections, which could theoretically be drawn only by hand. Previous systems put constraints on colors that need to be used to form the marker. The proposed system works with any saturated color, leading to better blending with the surrounding environment. The marker’s final shape is a rectangular area of a solid color with three lines of a different color going from the center to three corners of the rectangle. Precise detection can be achieved using neural networks, given that the training set is very varied and well designed. A detailed literature review was performed, and no such system was found. Therefore, the proposed design is novel for localization in the spatial scene. The testing proved that the system works well both indoor and outdoor, and the detections are precise.
A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm

The development of deep learning provides a new research method for fault diagnosis. However, in the industrial field, the labeled samples are insufficient and the noise interference is strong so that raw data obtained by the sensor are occupied with noise signal. It is difficult to recognize time-domain fault signals under the severe noise environment. In order to solve these problems, the convolutional neural network (CNN) fusing frequency domain feature matching algorithm (FDFM), called CNN-FDFM, is proposed in this paper. FDFM extracts key frequency features from signals in the frequency domain, which can maintain high accuracy in the case of strong noise and limited samples. CNN automatically extracts features from time-domain signals, and by using dropout to simulate noise input and increasing the size of the first-layer convolutional kernel, the anti-noise ability of the network is improved. Softmax with temperature parameter T and D-S evidence theory are used to fuse the two models. As FDFM and CNN can provide different diagnostic information in frequency domain, and time domain, respectively, the fused model CNN-FDFM achieves higher accuracy under severe noise environment. In the experiment, when a signal-to-noise ratio (SNR) drops to -10 dB, the diagnosis accuracy of CNN-FDFM still reaches 93.33%, higher than CNN’s accuracy of 45.43%. Besides, when SNR is greater than -6 dB, the accuracy of CNN-FDFM is higher than 99%.
Nanoradiopharmaceuticals Based on Alpha Emitters: Recent Developments for Medical Applications

The application of nanotechnology in nuclear medicine offers attractive therapeutic opportunities for the treatment of various diseases, including cancer. Indeed, nanoparticles-conjugated targeted alpha-particle therapy (TAT) would be ideal for localized cell killing due to high linear energy transfer and short ranges of alpha emitters. New approaches in radiolabeling are necessary because chemical radiolabeling techniques are rendered sub-optimal due to the presence of recoil energy generated by alpha decay, which causes chemical bonds to break. This review attempts to cover, in a concise fashion, various aspects of physics, radiobiology, and production of alpha emitters, as well as highlight the main problems they present, with possible new approaches to mitigate those problems. Special emphasis is placed on the strategies proposed for managing recoil energy. We will also provide an account of the recent studies in vitro and in vivo preclinical investigations of α-particle therapy delivered by various nanosystems from different materials, including inorganic nanoparticles, liposomes, and polymersomes, and some carbon-based systems are also summarized.
Mobile3DScanner: An Online 3D Scanner for High-quality Object Reconstruction with a Mobile Device

We present a novel online 3D scanning system for high-quality object reconstruction with a mobile device, called Mobile3DScanner. Using a mobile device equipped with an embedded RGBD camera, our system provides online 3D object reconstruction capability for users to acquire high-quality textured 3D object models. Starting with a simultaneous pose tracking and TSDF fusion module, our system allows users to scan an object with a mobile device to get a 3D model for real-time preview. After the real-time scanning process is completed, the scanned 3D model is globally optimized and mapped with multi-view textures as an efficient post process to get the final textured 3D model on the mobile device. Unlike most existing state-of-the-art systems which can only scan homeware objects such as toys with small dimensions due to the limited computation and memory resources of mobile platforms, our system can reconstruct objects with large dimensions such as statues. We propose a novel visual-inertial ICP approach to achieve real-time accurate 6DoF pose tracking of each incoming frame on the front end, while maintaining a keyframe pool on the back end where the keyframe poses are optimized by local BA. Simultaneously, the keyframe depth maps are fused by the optimized poses to a TSDF model in real-time. Especially, we propose a novel adaptive voxel resizing strategy to solve the out-of-memory problem of large dimension TSDF fusion on mobile platforms. In the post-process, the keyframe poses are globally optimized and the keyframe depth maps are optimized and fused to obtain a final object model with more accurate geometry. The experiments with quantitative and qualitative evaluation demonstrate the effectiveness of the proposed 3D scanning system based on a mobile device, which can successfully achieve online high-quality 3D reconstruction of natural objects with larger dimensions for efficient AR content creation.
Comparable Infection Level and Tropism of Measles Virus and Canine Distemper Virus in Organotypic Brain Slice Cultures Obtained from Natural Host Species

Measles virus (MV) and canine distemper virus (CDV) are closely related members of the family Paramyxoviridae, genus Morbillivirus. MV infection of humans and non-human primates (NHPs) results in a self-limiting disease, which rarely involves central nervous system (CNS) complications. In contrast, infection of carnivores with CDV usually results in severe disease, in which CNS complications are common and the case-fatality rate is high. To compare the neurovirulence and neurotropism of MV and CDV, we established a short-term organotypic brain slice culture system of the olfactory bulb, hippocampus, or cortex obtained from NHPs, dogs, and ferrets. Slices were inoculated ex vivo with wild-type-based recombinant CDV or MV expressing a fluorescent reporter protein. The infection level of both morbilliviruses was determined at different times post-infection. We observed equivalent infection levels and identified microglia as main target cells in CDV-inoculated carnivore and MV-inoculated NHP brain tissue slices. Neurons were also susceptible to MV infection in NHP brain slice cultures. Our findings suggest that MV and CDV have comparable neurotropism and intrinsic capacity to infect CNS-resident cells of their natural host species.
Self-Directed Exergaming for Stroke Upper Limb Impairment Increases Exercise Dose Compared to Standard Care

Background. One of the strongest modifiable determinants of rehabilitation outcome is exercise dose. Technologies enabling self-directed exercise offer a pragmatic means to increase dose, but the extent to which they achieve this in unselected cohorts, under real-world constraints, is poorly understood. Objective. Here we quantify the exercise dose achieved by inpatient stroke survivors using an adapted upper limb (UL) exercise gaming (exergaming) device and compare this with conventional (supervised) therapy. Methods. Over 4 months, patients presenting with acute stroke and associated UL impairment were screened at a single stroke centre. Participants were trained in a single session and provided with the device for unsupervised use during their inpatient admission. Results. From 75 patients referred for inpatient UL therapy, we recruited 30 (40%), of whom 26 (35%) were able to use the device meaningfully with their affected UL. Over a median enrolment time of 8 days (IQR: 5–14), self-directed UL exercise duration using the device was 26 minutes per day (median; IQR: 16–31), in addition to 25 minutes daily conventional UL therapy (IQR: 12–34; same cohort plus standard care audit; joint n = 50); thereby doubling total exercise duration (51 minutes; IQR: 32–64) relative to standard care (Z = 4.0, P <.001). The device enabled 104 UL repetitions per day (IQR: 38–393), whereas conventional therapy achieved 15 UL repetitions per day (IQR: 11–23; Z = 4.3, P <.001). Conclusion. Self-directed adapted exergaming enabled participants in our stroke inpatient cohort to increase exercise duration 2-fold, and repetitions 8-fold, compared to standard care, without requiring additional professional supervision.
Effects of Epichloë sinensis Endophyte and Host Ecotype on Physiology of Festuca sinensis under Different Soil Moisture Conditions

This study explored the effects of the Epichloë sinensis endophyte on growth, photosynthesis, ionic content (K+ and Ca2+), phytohormones (abscisic acid—ABA, cytokinin—CTK, indolE−3-acetic acid—IAA, and gibberellin—GA), and elements—C, N, P (in the shoot and root) in two ecotypes of Festuca sinensis (ecotypes 111 and 141) under different soil water conditions (35% and 65% relative saturation moisture content (RSMC)). The results showed that 35% RSMC inhibited the plants’ growth, and compared with 65% RSMC, there was a significant (p < 0.05) decrease in the growth and photosynthesis indices, the contents of CTK and GA, Ca2+ concentration, and the contents of C, N, and P (in both the aboveground and underground parts) under 35% RSMC. E. sinensis had beneficial effects on host growth and stress tolerance. Under both 35% and 65% RSMC, the presence of E. sinensis significantly (p < 0.05) increased host plant height, tiller number, root length, root volume, shoot dry weight, chlorophyll content, and the rate of photosynthesis of both ecotypes. Furthermore, the shoot C, N, and P contents in plants infected with E. sinensis (E+) from the two ecotypes, under both conditions of RSMC, were significantly (p < 0.05) higher than those in corresponding plants that were not infected with E. sinensis (E−). Under 35% RSMC, the contents of ABA, K+, Ca2+, and root P contents in E+ plants were significantly (p < 0.05) higher than those in corresponding E− plants in both ecotypes. However, under 65% RSMC, root C, N, and P contents in E+ plants of ecotype 111 and 141 were significantly (p < 0.05) higher than those in corresponding E− plants. In addition, the host ecotype also had effects on host growth and stress tolerance; the growth and photosynthetic indices of ecotype 141 were significantly (p < 0.05) higher than those of ecotype 111 under 35% RSMC, which suggested that ecotype 141 is more competitive than ecotype 111 under water deficiency conditions. These findings suggest that the endophyte improved the host plant resistance to water deficiency by maintaining the growth of the plant, improving photosynthesis, accumulating K+ and Ca2+, promoting nutrient absorption, and adjusting the metabolism of plant hormones.
Evidence-Based Practices and Implementation Science in Special Education

Establishing a process for identifying evidence-based practices (EBPs) in special education has been a significant advance for the field because it has the potential for generating more effective educational programs and producing more positive outcomes for students with disabilities. However, the potential benefit of EBPs is bounded by the quality, reach, and maintenance of implementation. The cross-disciplinary field of implementation science has great relevance for translating the promise of EBPs into positive outcomes for children and youth with disabilities. This article examines the history, extent, and limitations of EBPs and describes the emergence and current state of implementation science as applied in special education. Subsequent articles in this special issue of Exceptional Children address a range of issues related to implementation science in special education: the research-to-practice gap, dissemination and diffusion, adherence and sustainability, scaling up, a model for state-level implementation, and fostering implementation through professional development.
Making Entrepreneurs? Makerspaces and Entrepreneurial Intent Among High School Students

Makerspaces have grown over the last two decades and provide a potentially important resource to entrepreneurs. One area where the expansion of makerspaces has been the largest is in educational settings, at both K-12 schools and colleges. However, scant research to date has analysed whether students visiting a makerspace have any relationship with their professional goals or intentions. This study uses a survey conducted in New Orleans to analyse the predictors of what students use a makerspace, and the potential relationship visiting may have with entrepreneurial intent. The analysis finds that students with a higher socio-economic status appear to use makerspaces more often, and that students who visited makerspaces are more likely to express interest in starting their own businesses.
Effects of Thermal Radiation on Transient MHD Free Convection Flow over a vertical Surface embedded in a Porous Medium with Periodic Boundary Temperature

This paper investigates the effects of thermal radiation on transient MHD free convection flow over a vertical surface embedded in a porous medium with periodic temperature. Analytical solutions are obtained for the governing coupled dimensionless partial differential equations of velocity and temperature. The results are discussed with the effects of various dimensionless parameters such as R, radiation; M, magnetic; χ, porosity and âÂ¦τ , phase angle for the Prandtl number, P r = 0.71 which represents air at 20o C and of 1 atmospheric pressure. The results showed sensitive dependence on the parameters. Also, quantitative discussions are presented for the Skin friction and Heat flux
Weak Contractions for Initial Value Problems

Piyachat Borisut 1 , Poom Kumam 1,2,* , Vishal Gupta 3 and Naveen Mani 3 1 KMUTT-Fixed Point Research Laboratory, Room SCL 802 Fixed Point Laboratory, Science Laboratory Building, Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok 10140, Thailand; piyachat.b@hotmail.com 2 KMUTT-Fixed Point Theory and Applications Research Group, Theoretical and Computational Science Center (TaCS), Science Laboratory Building, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok 10140, Thailand 3 Department of Mathematics, Maharishi Markandeshwar (Deemed to be University), Mullana 133207, Haryana, India; vishal.gmn@gmail.com (V.G.); naveenmani81@gmail.com (N.M.) * Correspondences: poom.kum@kmutt.ac. th
ELECTRICALLY SMALL RADIATION PATTERN RECONFIGURABLE ANTENNA WITH EXPANDED BANDWIDTH AND HIGH FRONT-TO-BACK RATIO

This paper presents an electrically small antenna (ka = 0.87) with ultra-low-profile 0. 005λ0 and six reconfigurable endfire radiation patterns, which cover the entire 360◦ azimuth plane. An equivalent magnetic dipole and six switchable equivalent electric dipoles achieve the six reconfigurable endfire radiation patterns by switching the ON/OFF states of six PIN diodes. The designing bright point is the dual side printed loop, that is, an Alford loop and six loaded circular arc stubs, which form the equivalent magnetic dipole. This technique can reduce the size by 77% compared with single side printed loop, expand the bandwidth, and produce a strong and uniform near magnetic field, which leads to a high F/B ratio. Compared with published pattern-reconfigurable ESAs with endfire radiation characteristics, the proposed antenna has higher F/B ratio about 35.6 dB, more switchable states and expanded bandwidth. In addition, the measured peak realized gain and radiation efficiency at 1.5 GHz are 3.52 dBi and 77.6%, respectively.
A Graphical Interface for Curating Schemas

Much past work has focused on extracting information like events, entities, and relations from documents. Very little work has focused on analyzing these results for better model understanding. In this paper, we introduce a curation interface that takes an Information Extraction (IE) system’s output in a pre-defined format and generates a graphical representation of its elements. The interface supports editing while curating schemas for complex events like Improvised Explosive Device (IED) based scenarios. We identify various schemas that either have linear event chains or contain parallel events with complicated temporal ordering. We iteratively update an induced schema to uniquely identify events specific to it, add optional events around them, and prune unnecessary events. The resulting schemas are improved and enriched versions of the machine-induced versions.
The importance of physical activity for the development of motor skills of younger school age children

Physical activity plays an important role in the motor and psychological development in a pediatric population. The maturation of human motor skills is gradual over the time. It depends on several factors, including but not limited to: individual differences, health condition, quality of neuromuscular structures and stimulating factors. Research included in this review shows that different types of physical activity, including aerobic training, strength training, dance, yoga, and walking programs, improve mood and mental health. Aerobic physical activity has the greatest effect on reducing the symptoms of anxiety and stress. Habits related to the physical activity, acquired in childhood, can be maintained in adulthood, which contributes to the better health and quality of life. Extensive literature indicates that regular physical activity encourages growth and development and has multiple benefits for the mental, physical, cognitive and psychosocial health of children. Children capacities for exercise change in accordance within defined developmental periods. Young children are active at short intervals and their capacity for continuous activity increases as they grow and mature. The health benefits of sporadic exercise at a younger age are not well established, stressing the short-term benefits of physical activity for some aspects of cognitive and mental health, indicating that maximum benefit can be achieved by frequent bouts of exercise during the day.