Miracle-dz/UniFAR-FTUs huggingface dataset:
An Optimal Authentication Scheme through Dual Signature for the Internet of Medical Things

The Internet of Medical Things (IoMT) overcomes the flaws in the traditional healthcare system by enabling remote administration, more effective use of resources, and the mobility of medical devices to fulfil the patient’s needs. The IoMT makes it simple to review the patient’s cloud-based medical history in addition to allowing the doctor to keep a close eye on the patient’s condition. However, any communication must be secure and dependable due to the private nature of patient medical records. In this paper, we proposed an authentication method for the IoMT based on hyperelliptic curves and featuring dual signatures. The decreased key size of hyperelliptic curves makes the proposed scheme efficient. Furthermore, security validation analysis is performed with the help of the formal verification tool called Scyther, which shows that the proposed scheme is secure against several types of attacks. A comparison of the proposed scheme’s computational and communication expenses with those of existing schemes reveals its efficiency.
Bone Fractured X-ray Data Generation Based on DCGAN

As the global population of elderly individuals is expected to double by 2050, the incidence of bone fractures is likely to increase, posing a significant public health concern. To address this issue, researchers have increasingly turned to Artificial Intelligence (AI) technology to facilitate medical treatments. However, obtaining sufficient patient illness images to train AI models remains a challenge. This study uses Deep Convolutional Generative Adversarial Network (DCGAN) to generate X-ray picture to help solve this problem. This study built DCGAN by doing some changes basing on original DCGAN. This study built the Generator and Discriminator by using five layers fractionally-strided convolutions and five layers Convolutional Neural Network (CNN). Both of the fractionally-strided convolutions and CNN are built with 44 size of kernels, 1 length of stride and the padding is 1. However, the padding in the last layer of Discriminator and the first layer of Generator is 0. When built the Discriminator, this study used SilU as the activation function instead of LeakReLU. Being trained by using the bone fractures X-ray data set from Kaggle, the model obtains a satisfactory result. The final loss of the Generator is 1.9012 and the final loss of the Discriminator is 0.8281. Although the generated images were somewhat indistinguishable from the original data, they bore a striking resemblance to the actual X-ray images.
Generalized Degrees of Freedom for Gaussian Interference Channel with Discrete Constellations

Generalized Degrees of Freedom for Gaussian Interference Channel with Discrete Constellations Chu Pang Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2012 In wireless channels and many other channels, interference is a central phenomenon. Mitigating interference is a key to improving system performance. To find the limit of the achievable rates for these channels in the presence of interference, the two-user Gaussian interference channel has been the subject of intensive study in network information theory. However, most current results have been obtained by assuming Gaussian input distributions. While optimal in single-user Gaussian channels, the issue with this assumption is that the Gaussian noise becomes the worst noise when the input distribution is also Gaussian. In this thesis, we propose a class of discrete constellations. We show that this class of constellations can automatically achieve the same sum rates as schemes that treat interference as noise or perform time sharing.
Hydrodynamic dispersion in a tube with diffusive losses through its walls

Advective–diffusive transport of passive or reactive scalars in confined environments (e.g. tubes and channels) is often accompanied by diffusive losses/gains through the confining walls. We present analytical solutions for transport of a reactive solute in a tube, whose walls are impermeable to flow but allow for solute diffusion into the surrounding medium. The solute undergoes advection, diffusion and first-order chemical reaction inside the tube, while diffusing and being consumed in the surrounding medium. These solutions represent a leading-order (in the radius-to-length ratio) approximation, which neglects the longitudinal variability of solute concentration in the surrounding medium. A numerical solution of the full problem is used to demonstrate the accuracy of this approximation for a physically relevant range of model parameters. Our analysis indicates that the solute delivery rate can be quantified by a dimensionless parameter, the ratio of a solute’s residence time in a tube to the rate of diffusive losses through the tube’s wall.
A Novel Integrated Simulation Framework for Cyber-Physical Systems Modelling

The growing use of Cyber-Physical Systems (CPS) in a plethora of domains (e.g. healthcare, industry, smart homes, transportation, etc.) triggers an urgent demand for simulation frameworks that can simulate in an integrated manner all the components (i.e. CPUs, Memories, Networks, Physical Environment) of a system-under-design(SuD). By utilizing such a simulator, software design can proceed in parallel with physical development which results in the reduction of the so important time-to-market. The main problem, however, is that currently there is a shortage of such simulation frameworks; most simulators used for modelling the digital aspects of CPS applications (i.e. full-system CPU/Mem/Peripheral simulators) lack any support of the CPS physical aspects and vice versa. The presented fully-distributed simulation framework (APOLLON) is the first known open-source, high-performance simulator that can handle holistically complex CPSs including processors, peripherals, networks and physical aspects of them. APOLLON is an extension of the COSSIM simulation framework and it integrates, in a novel and efficient way, a combined processing and network simulator with the widely-used Ptolemy physical simulator, in a transparent way. Our highly integrated approach is further augmented with Machine Learning capabilities by implementing Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) recurrent neural networks in both the Cyber and Physical domains, enabling users to develop their complex recurrent neural networks significantly fast and accurately. APOLLON has been evaluated when executing a number of benchmarks and real-world use cases; the end results demonstrate that the presented approach has up to 99% accuracy in the reported SuD aspects.
On the Teaching and Learning of Fractions through a Conceptual Generalization Approach

This paper deals with precursory (propaedeutic) learning of the concept of number in the elementary mathematical education. The authors’ objective is to suggest a method allowing for the increase of the effectiveness of interactive expansion of the concept of number by using a grade-appropriate learning framework for elementary mathematical education content. A theoretical background for the creation of this method is based on the description of various characteristics of precursory learning and interactive teaching of mathematics as well and the flexible differentiation approach. The paper especially emphasizes the possibilities of propaedeutic understanding of the concept of fraction and examine the effects of such approach in terms of student achievement in elementary mathematics education, on the basis of a methodological approach. Results obtained during the experimental research suggest that under the influence of the methodological approach of introducing fractions through propaedeutic learning, students achieve significantly better results in learning compared to students who have not used this method.
Comparing the Anterior-Based Muscle-Sparing Approach with the Direct Anterior Approach in Hip Arthroplasty: A Systematic Review and Pairwise Meta-Analysis

Background and Objectives: The anterior-based muscle-sparing (ABMS) approach, which utilizes the interval between the tensor fasciae latae posteriorly, offers several advantages, such as the reduced risk of nerve injury and the freedom to choose various implants. Herein, we aimed to compare the outcome of ABMS to the direct anterior (DA) approach using pairwise meta-analysis techniques. Materials and Methods: A systematic search of the MEDLINE (PUBMED), Embase, and Cochrane Library databases was performed for studies published up to 7 June 2023, which compared the ABMS approach with the DA approach for hip arthroplasty. We compared (1) perioperative outcomes (operation time, visual analog scale (VAS) score, total opioid consumption, length of hospital stay (LOS), and the number of patients discharged to their homes); (2) postoperative complications (neuropraxia/nerve injury, dislocation, surgical site infection, intraoperative fracture, and reoperation rate); and (3) implant position (cup inclination, cup anteversion, and stem alignment). Results: Ten studies were eligible for meta-analysis, including 1737 patients who underwent hip arthroplasty with the ABMS approach and 1979 with the DA approach. The pooled analysis showed no differences in all outcome variables, including perioperative outcomes, postoperative complications, and the implant position between the two surgical approaches. Conclusions: In current meta-analysis, the ABMS approach demonstrated comparable results to the conventional DA approach in terms of both clinical and radiologic outcomes as well as postoperative complications. Furthermore, the ABMS approach has the advantage of a broader indication and fewer limitations in terms of the surgical position compared to the DA approach. Therefore, the ABMS approach can be even more beneficial as an option within MSA, surpassing the utility of the DA approach.
Relationships between reference site quality and baetid mayfly assemblages in mountainous streams of the Luvuvhu catchment, South Africa

With water quality deteriorating rapidly at a global scale, river sections suited to serve as reference sites are being increasingly lost. It thus becomes critical to develop rapid methods to confirm that previously monitored sites continue meet the requirements of reliable reference sites. In the absence of pristine sites, 9 near-natural sites, as defined by the Kleynhans (1996) classification, were used as reference sites for the Luvuvhu River catchment to compare the quality of physico-chemical factors against a biological metric. Baetid mayfly community structure at a site was chosen as an index of water quality, since this family is common in all types of freshwaters, highly diverse and adapted to unpolluted running water. Baetid larvae were sampled monthly from stones-in-current biotopes across 9 sites for over 1 year, between December 2016 and January 2018. A Spearman’s correlation test was used to evaluate the relationship between physico-chemical factors and identify redundant variables. Water quality standards were measured against the national water quality guidelines for aquatic ecosystems. We used a generalized linear model to determine the effect of physico-chemical variables on baetid species, and canonical correspondence analysis to show the relationships between baetid species, sites, and physico-chemical variables. A total of 3 039 individuals belonging to 12 mayfly species were recorded. Our findings indicated that while the physico-chemical factors were highly variable, they were within favourable ranges to reflect reference site conditions. While water temperature was the most important driver of baetid community structure in general, as it negatively affected their abundances, a subset of species (Pseudoponnota sp., Pseudocloeon sp., Acanthiops varius and Demoulinia crassi) showed clear responses to changes in TDS and stream width. We conclude that specific baetid species show good potential as biological indicators of reference sites and chronic water temperature stress, making assessment of reference sites easier.
Other-Benefiting Lying Behavior in Preschool Children and Its Relation to Theory of Mind and Empathy

The present study examined children’s lies to help others obtain benefits (other-benefiting lying) and its relation to theory of mind (ToM) and empathy among 3–5-year-old preschool children. One hundred nine children were recruited from preschools in China. A modified hide-and-seek paradigm was used to measure children’s other-benefiting lying behavior, a ToM scale was used to measure children’s ToM abilities, and an empathy scale was used to measure children’s empathy abilities. Results showed that children tended to tell more lies to help other to get benefits as age increased, and further analyses showed that this other-benefiting lying was related to children’s ToM component of false belief understanding and their cognitive empathy performance. These findings provide evidence that cognitive factors play important roles in children’s lying to help others.
Structural damage detection based on l1 regularization using natural frequencies and mode shapes

Conventional vibration‐based damage detection methods employ the Tikhonov regularization in model updating to deal with the problems of underdeterminacy and measurement noise. However, the Tikhonov regularization technique tends to provide over smooth solutions that the identified damage is distributed to many structural elements. This result does not match the sparsity property of the actual damage scenario, in which structural damage typically occurs at a small number of locations only in comparison with the total elements of the entire structure. In this study, an l1 regularization‐based model updating technique is developed by utilizing the sparsity of the structural damage. Both natural frequencies and mode shapes are employed during the model updating. A strategy of selecting the regularization parameter for the l1 regularization problem is also developed. A numerical and an experimental examples are utilized to demonstrate the effectiveness of the proposed damage detection method. The results showed that the proposed l1 regularization‐based method is able to locate and quantify the sparse damage correctly over a large number of elements. The effects of the mode number on the damage detection results are also investigated. The advantage of the present l1 regularization over the traditional l2 regularization method in damage detection is also demonstrated.
An Efficient Sampling Algorithm for Network Motif Detection

ABSTRACT We propose a sequential importance sampling strategy to estimate subgraph frequencies and detect network motifs. The method is developed by sampling subgraphs sequentially node by node using a carefully chosen proposal distribution. Viewing the subgraphs as rooted trees, we propose a recursive formula that approximates the number of subgraphs containing a particular node or set of nodes. The proposal used to sample nodes is proportional to this estimated number of subgraphs. The method generates subgraphs from a distribution close to uniform, and performs better than competing methods. We apply the method to four real-world networks and demonstrate outstanding performance in practical examples. Supplemental materials for the article are available online.
Realistic simulations of a cyclotron spiral inflector within a particle-in-cell framework

We present an upgrade to the particle-in-cell ion beam simulation code OPAL that enables us to run highly realistic simulations of the spiral inflector system of a compact cyclotron. This upgrade includes a new geometry class and field solver that can handle the complicated boundary conditions posed by the electrode system in the central region of the cyclotron both in terms of particle termination, and calculation of self-fields. Results are benchmarked against the analytical solution of a coasting beam. As a practical example, the spiral inflector and the first revolution in a 1 MeV=amu test cyclotron, located at Best Cyclotron Systems, Inc., are modeled and compared to the simulation results. We find that OPAL can now handle arbitrary boundary geometries with relative ease. Simulated injection efficiencies and beam shape compare well with measured efficiencies and a preliminary measurement of the beam distribution after injection.
Polarimetry: a primary tool for the physical characterization of asteroids

Abstract Asteroid polarimetry has taken profit in recent years of a renewed interest triggered by exciting results from observing campaigns and theoretical studies. One of the most important applications of polarimetry to asteroid studies is the derivation of the geometric albedo and of the typical sizes of the particles forming the regolith layer covering the surface. Moreover, the serendipitous discovery of a new class of asteroids displaying unusual polarimetric properties, the so-called “Barbarians”, has been followed by increasing evidence that these objects can be extremely primitive and may be interpreted as remnants of the very first generation of solid bodies accreted in the inner Solar System. In addition, some results of asteroid polarimetry are going to be interpreted, for the first time, in terms of some “ground truth” evidence, made possible by in situ observations of the surface of the asteroid (4) Vesta by the Dawn space probe. Finally, some preliminary evidence suggests that spectro-polarimetry is going to become a major tool for the physical characterization of the small bodies of the solar system.
Corundum-bearing and spinel-bearing symplectites in ultrahigh-pressure eclogites record high-temperature overprint and partial melting during slab exhumation

Abstract. Corundum- and spinel-bearing symplectites after muscovite were found in ultrahigh-pressure (UHP) eclogites from the Dabie terrane, China. Three types of symplectites were recognized based on their mineral assemblages: (1) symplectitic intergrowths of corundum + plagioclase + biotite after phengite (CPB), (2) symplectitic intergrowths of spinel + plagioclase + biotite after phengite (SPB), and (3) symplectitic intergrowths of spinel + plagioclase after paragonite (SP). The microtextures and mineral assemblages of the symplectites, in combination with the results of thermodynamic modeling on local regions, indicate that these symplectites formed by the breakdown of phengite and paragonite during the granulite-facies metamorphic overprint (770–850 ∘C) of the eclogite at pressures of 0.8–0.9 GPa. Dehydration partial melting reactions occurred during the breakdown of muscovite, which leads to the formation of thin plagioclase films (silicate melts) along grain (garnet, rutile, quartz) boundaries. Mass balance calculations indicate that the development of CPB and SPB symplectites after phengite requires the introduction of Al, Ca, Na, and Fe and loss of Si, Mg, and K. However, the formation of SP symplectites after paragonite requires the input of Mg, Ca, and Fe and removal of Si, Al, and Na. By summarizing the occurrence and growth mechanism of corundum- and spinel-bearing symplectites in global UHP terranes, we find that such symplectites can form by both the subsolidus replacement of an Al-rich anhydrous mineral (kyanite) and the dehydration melting of an Al-rich hydrous phase during high-temperature metamorphism. This study reveals that muscovite-bearing eclogites may experience multiple episodes of partial melting during the slab exhumation, not only at the high-pressure (HP) exhumation stage but also at the lower-pressure metamorphic overprinting stage. Kyanite is a reaction product during the HP partial melting, whereas the low-pressure (LP) melting will consume kyanite. We propose that the occurrence of corundum- and spinel-bearing symplectites after muscovite in eclogites is a potential mineralogical indicator of LP melting in exhumed slabs.
Effects of ketogenic diet on the classification and functional composition of intestinal flora in children with mitochondrial epilepsy

The ketogenic diet (KD) has shown excellent performance in the treatment of refractory epilepsy, but how it works is not yet fully understood. Gut microbiota is associated with various neurological disorders through the brain-gut axis. Different dietary patterns have different effects on the composition and function of gut microbiota. Here, by analyzing fecal samples from some patients with mitochondrial epilepsy before and after KD treatment through 16SrRNA sequencing, we found that KD intervention reduced the abundance of Firmicutes in the patient’s gut, while the abundance of Bacteroidota increased in the KD group. LefSe analysis showed that Actinobacteriota, Phascolarctobacterium had significant advantages in the control group, while Bacteroides increased significantly after KD intervention, especially Bacteroides fragilis. Functional analysis showed that there were significant differences in 12 pathways in level 3. These changes suggest that KD can change the composition and diversity of the gut microbiota in patients and affect their function. Changes in specific bacterial groups in the gut may serve as biomarkers for the therapeutic effects of KD on epilepsy.
Contribution of image processing for analyzing the cellular structure of cork

The alveolar structure of cork confers to this natural material specific physical properties such as low permeability to liquids and gases, advanced thermal and acoustic insulation, and high elasticity. In this paper, a morphological analysis of natural cork cells is presented including statistical distributions of structural quantities. These results were obtained from the study of scanning electron microscopy images of natural cork stoppers. After automation of the image processing analysis, the area and perimeter distributions were measured in different cork sections: axial, tangential, and radial. Perpendicular to the radial direction we also focused on growth rings, which are characterized by smaller cell sizes. This systematic image analysis offers new possibilities to investigate the material at the cell scale and provides useful statistical information about the cork structure.