Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximum Likelihood Estimation in Generalized Rasch Models

We review various models and techniques that have been proposed for item analysis according to the ideas of Rasch. A general model is proposed that unifies them, and maximum likelihood procedures are discussed for this general model. We show that unconditional maximum likelihood estimation in the functional Rasch model, as proposed by Wright and Haberman, is an important special case. Conditional maximum likelihood estimation, as proposed by Rasch and Andersen, is another important special case. Both procedures are related to marginal maximum likelihood estimation in the structural Rasch model, which has been studied by Sanathanan, Andersen, Tjur, Thissen, and others. Our theoretical results lead to suggestions for alternative computational algorithms.
Mathematical Optimisation of Magnetic Nanoparticle Diffusion in the Brain White Matter

Magnetic nanoparticles (MNPs) are a promising drug delivery system to treat brain diseases, as the particle transport trajectory can be manipulated by an external magnetic field. However, due to the complex microstructure of brain tissues, particularly the arrangement of nerve fibres in the white matter (WM), how to achieve desired drug distribution patterns, e.g., uniform distribution, is largely unknown. In this study, by adopting a mathematical model capable of capturing the diffusion trajectories of MNPs, we conducted a pilot study to investigate the effects of key parameters in the MNP delivery on the particle diffusion behaviours in the brain WM microstructures. The results show that (i) a uniform distribution of MNPs can be achieved in anisotropic tissues by adjusting the particle size and magnetic field; (ii) particle size plays a key role in determining MNPs’ diffusion behaviours. The magnitude of MNP equivalent diffusivity is reversely correlated to the particle size. The MNPs with a dimension greater than 90 nm cannot reach a uniform distribution in the brain WM even in an external magnitude field; (iii) axon tortuosity may lead to transversely anisotropic MNP transport in the brain WM; however, this effect can be mitigated by applying an external magnetic field perpendicular to the local axon track. This study not only advances understanding to answer the question of how to optimise MNP delivery, but also demonstrates the potential of mathematical modelling to help achieve desired drug distributions in biological tissues with a complex microstructure.
Effect of limestone usage on tribological properties in copper and asbestos-free brake friction materials

Purpose This study aims to determine the braking performance of limestone as a filler in brake friction materials. Design/methodology/approach Samples containing limestone material (30-35-40%), which can be an alternative to brake friction material filler, were produced. The samples were weighed on precision scales, mixed homogeneously and produced using the hot molding method. The physical and tribological properties of the produced samples were determined, and their microscopic analyzes were made with scanning electron microscopy. Findings As the amount of limestone increased, the density of the samples decreased. The friction coefficient and wear rates were close to each other and within the optimum limits for all samples. Limestone materials can be used instead of barite materials studied in the literature on brake linings. Microcracks were observed only in samples containing 30% and 35% limestone in microscopic images. Originality/value In this study, the wear rate, coefficient of friction and microstructures on the friction surfaces of brake friction materials containing limestone were investigated. The usability of limestone as a filler in brake friction materials provides valuable information to researchers and industrial organizations in the brake friction material field.
Customized EfficientNet for Histopathology Image Representation

In recent years, and amplified by the COVID-19 pandemic, the digitization of pathology has gained a considerable attention. Digital pathology provides crucial advantages compared to conventional light microscopy, including more efficient workflows, more accurate diagnosis and treatment planning, and easier collaboration. Despite promising progress, there are some critical challenges related to classifying images in digital pathology, such as huge input sizes (e.g., gigapixels) and expensive processing time. Most of the existing models for classification of histopathology images are very large and accordingly have many parameters to be learned/optimized. In addition, due to the large size of Whole Slide Images (WSIs), e.g., 100,000 × 100,000 pixels, models require enormous computational times to achieve reliable results. In order to address these challenges, we propose a more compact network which is customized to classify cancer subtypes with lower computation time and memory complexity. This model is based on EfficientNet topology, but it is tailored for classifying histopathology images. The utilized model is evaluated over three tumor types brain, lung, and kidney from The Cancer Genome Atlas (TCGA) public repository. Since the pre-trained EfficientNet works properly with the specific size of images, an effective approach is proposed to adjust the size of input images. The proposed model can be trained with a much smaller training set for applications such as image search that require robust and compact representations. The results show that the proposed model, compared to state-of-the-art models, i.e., KimiaNet, can classify cancer subtypes more accurately and provides superior results. In addition, the proposed model achieves memory and computational efficiency in the training phase and is a more compact deep topology compared to KimiaNet.
Development of hot slumping technique and last optical performances obtained on a 500mm diameter slumped segment prototype for adaptive optics

In the framework of the E-ELT Design Study financed by the European Community under OPTICON-FP6, the INAF Astronomical Observatory of Brera (INAF-OAB) has developed a technique for the manufacturing of thin optical segments. Thin glass segments are produced by mean of an hot slumping technique that makes use of an optical quality ceramic mould and a precise thermal circle to impart the desired shape to a glass sheet. In the present paper we summarize the results obtained during this study and report the last results of the effort in scaling-up the procedure: in particular the overall process has been refined in order to optimize the parameters (such as time, maximum temperature and amount of pressure) used to slump a 500 mm diameter glass segment. The thickness of these glass segments is of about 1.7 mm, making the optical surface very floppy and easy to be deformed. For this reason optical tests have been performed using a astatic support implemented into a vertical optical bench.
Random lasing from a nanoparticle-based metal–dielectric–dye medium

We report on enhancement of random laser operation due to surface plasmon (SP) effects from the addition of Ag nanoparticles to an Al2O3 scatterer based random laser. SP resonance provides a localized electromagnetic field enhancement near the surface of the Ag particle, which results in the creation of an enhanced gain region at the particle’s surface. The hybrid dye–dielectric–metallic nanoparticle random laser’s emission characteristics are investigated as a function of Ag particle concentration and pump energy fluence. When operating in the modestly scattering regime, the hybrid Ag and Al2O3 scatterer based random laser experiences an increase in peak emission intensity, and a decrease in the emission linewidth with the addition of Ag particles.
Rare Variants of Dermatofibrosarcoma Protuberans: Clinical, Histologic, and Molecular Features and Diagnostic Pitfalls

Dermatofibrosarcoma protuberans (DFSP) is a dermal malignant mesenchymal tumor. Most variants are associated with a high risk of local recurrence and a low risk of metastasis. The classic histomorphology of this tumor is made up of uniform, spindle-shaped cells, arranged in a storiform pattern. Tumor cells characteristically infiltrate the underlying subcutis in a honeycomb pattern. Less common variants of DFSP have been identified: myxoid, pigmented, myoid, granular cell, sclerosing, atrophic, and fibrosarcomatous. Only the fibrosarcomatous variant has been shown to differ significantly from classic DFSP in terms of clinical outcome; fibrosarcomatous DFSP has been shown to be associated with a greater risk of local recurrence and metastatic potential than classic DFSP. However, the other variants may pose diagnostic difficulty as they resemble other types of spindle cell neoplasms, especially in small biopsy specimens. This article reviews the clinical, histologic, and molecular features of DFSP variants, as well as possible pitfalls in their diagnosis and how to resolve them.
Revisiting Echo State Networks for Continuous Gesture Recognition

Smartphones are equipped with Inertial Measurement Units (IMUs) that can capture user gesture data. Continuous gesture recognition is essential as it can be utilized and enhance human-computer interaction. Echo State Networks (ESNs) and Long Short-Term Memory (LSTM) models are well suited to performing this task. They have been successfully applied to the task in previous research, with LSTMs outperforming ESNs while having a considerably longer training time. However, the application of ESNs to continuous gesture recognition has not been fully explored as only the leaky integrator ESN has been used without hyperparameter optimization. In this study, we attempt to improve the ESN performance on the continuous gesture recognition task by experimenting with different model architectures and hyperparameter tuning. The performance of ESN models is significantly enhanced in terms of $F_{1}$ -score to 0.88, which is higher than the previously best performance of 0.87 using an LSTM model on continuous gesture recognition. The significant improvement is in training time, which is approximately 13 seconds for the ESN model compared to 89 seconds for the LSTM model in past research.
Modeling and Characterization of Pre-Charged Collapse-Mode CMUTs

Recently, the applications of ultrasound transducers expanded from high-end diagnostic tools to point of care diagnostic devices and wireless power receivers for implantable devices. These new applications additionally require that the transducer technology must comply to biocompatibility and manufacturing scalability. In this respect, Capacitive Micromachined Ultrasound Transducers (CMUTs) have a strong advantage compared to the conventional PZT based transducers. However, current CMUTs require a large DC bias voltage for their operation, which limits the miniaturizability of these devices. In this study, we propose a pre-charged collapse-mode CMUT for immersive applications that can operate without an external bias by means of a charge trapping Al2O3 layer embedded in the dielectrics between the top and bottom electrodes. The built-in charge layer was analytically modeled and four layer stack combinations were investigated and characterized. The measurement results of the CMUTs were then used to fit the model and to quantify the amount and type of trapped charge. It was found that these devices polarize due to the ferroelectric-like behavior of the Al2O3, and the amount of charge stored in the charge-trapping layer was estimated to be approximately 0.02 C/m2. Their acoustic performance shows a transmit and receive sensitivity of 8.8 kPa/V and 13.1 V/MPa respectively. In addition, we show that increasing the charging temperature, the charging duration, and the charging voltage results in a higher amount of stored charge. Finally, results of ALT tests showed that these devices have a lifetime of more than 2.5 years at body temperature.
On the acoustics of tuning forks

Tuning forks can vibrate in many different modes in which the tines move either in the plane or perpendicular to the plane of the fork. Symmetrical modes can be modeled by the motion of two cantilever beams, antisymmetrical modes by the motion of a beam with free ends. A tuning fork vibrating in its fundamental mode is approximately a linear quadrupole sound source whose strength can be increased by use of a baffle or by touching the stem to a soundboard. The motion of the stem includes strong components at both the fundamental frequency and its second harmonic. Slight alterations in a tuning fork can enhance or suppress either of these components. At large amplitudes, the tines vibrate nonsinusoidally, the nth harmonic increasing approximately as the nth power of the fundamental.
License Plate Recognition System Based on Improved YOLOv5 and GRU

Aiming at the problem that the traditional license plate recognition method lacking of accuracy and speed, an end-to-end deep learning model for license plate location and recognition in natural scenarios was proposed. First, we added an improved channel attention mechanism to the down-sampling process of the You only look once(YOLOv5). Additionally, a location information is added in the ones to minimize the information loss from sampling, which can improve the feature extraction ability of the model. Then we reduce the number of parameters on the input side and set only one class in the YOLO layer, which improves the efficiency and accuracy of the detector for locating license plates. Finally, Gated recurrent units(GRU) + Connectionist temporal classification(CTC) was used to build the recognition network to complete the character segmentation-free recognition task of the license plate, significantly shortened the training time and improved the convergence speed and recognition accuracy of the network. The experimental results show that the average recognition precision of the license plate recognition model proposed in this paper reaches 98.98%, which is significantly better than the traditional recognition algorithm, and the recognition effect is good in complex environment with good stability and robustness.
The Ability of NiFe2O4 Samples to Reduce Electromagnetic Wave Pollution in the Frequency Range of 2-18 Ghz

Rapid technological developments have the impact of increasing electromagnetic wave pollution. To reduce this pollution, nickel ferrite (NiFe2O4) nanoparticles are made by using mechanical alloying method with high energy milling in a wet state. X-ray diffractometer was used to characterize the crystal structure and the formed phase; scanning electron microscopy was used to characterize surface morphology; and for magnetization, a vibrating sample of magnetometer was used. Meanwhile, the capability to absorb electromagnetic waves in the 2-18 GHz interval was using a vector network analyzer. NiFe2O4 nanoparticles have a cubic structure, space group Fd-3m, and a crystal size of 127 nm. The shape of the particles resembles a block and is spherical, measuring about 250-300 nm. At room temperature, NiFe2O4 nanoparticles are soft magnetic materials with a magnetic saturation (Ms) of 41.61 emu/g and a coercivity (Hc) of 0.24 kOe. The ability to absorb microwaves, is expressed by reflection loss (RL) ~ -25.81 dB at a frequency (f) 5.16 GHz with a bandwidth (BW) 1.62 GHz, while RL ~ - 18.64 dB at f = 10, 98 GHz with BW = 1.42 GHz.
Advances in the Biosynthesis and Molecular Evolution of Steroidal Saponins in Plants

Steroidal saponins are an important type of plant-specific metabolite that are essential for plants’ responses to biotic and abiotic stresses. Because of their extensive pharmacological activities, steroidal saponins are also important industrial raw materials for the production of steroidal drugs. In recent years, more and more studies have explored the biosynthesis of steroidal saponins in plants, but most of them only focused on the biosynthesis of their molecular skeleton, diosgenin, and their subsequent glycosylation modification mechanism needs to be further studied. In addition, the biosynthetic regulation mechanism of steroidal saponins, their distribution pattern, and their molecular evolution in plants remain unclear. In this review, we summarized and discussed recent studies on the biosynthesis, molecular regulation, and function of steroidal saponins. Finally, we also reviewed the distribution and molecular evolution of steroidal saponins in plants. The elucidation of the biosynthesis, regulation, and molecular evolutionary mechanisms of steroidal saponins is crucial to provide new insights and references for studying their distribution, diversity, and evolutionary history in plants. Furthermore, a deeper understanding of steroidal saponin biosynthesis will contribute to their industrial production and pharmacological applications.
MPCNet: Improved MeshSegNet Based on Position Encoding and Channel Attention

In the process of orthodontic treatment, it is a very important step to accurately segment each tooth and jaw model with computer assistance. The use of deep learning technology methods for tooth segmentation can not only save a lot of manual interaction and time cost but also improve the treatment effect. 3D tooth segmentation is a hot topic of interest for international related scholars, and some end-to-end tooth segmentation methods based on dental mesh scanning models have been emerging in recent years. Due to the limited variety of existing models, they are not well suited for different 3D segmentation scenarios, and the feature extraction capability and segmentation effect of these models still need to be improved. In this paper, we propose a novel end-to-end tooth segmentation method, MPCNet, which adds multi-scale mesh density information to the input layer, uses position encoding and channel attention mechanism to improve MeshSegNet, and uses graph-cut post-processing to perform 3D tooth segmentation in real scenes. The effectiveness of MPCNet is evaluated on a real 3D scanned tooth segmentation dataset, which significantly outperforms the current mainstream segmentation methods.
Design of V-band Diplexer Based on Electro-magnetic Band Gap Structure

In this paper, a V-band diplexer with high isolation and short branches characteristic is introduced. A bandpass filter (BPF) is connected to the common port of the diplexer, and stopband filters (BSFs) based on electromagnetic band gap (EBG) structure are inserted into the branches to achieve the characteristics of high isolation and short branches of the diplexer. The isolation and passband of the diplexer can be changed by adjusting the dimensions of EBG structure. The simulation results show that the maximum insertion losses are 1.15 dB and 1.19 dB at the center frequency of 60 GHz and 65 GHz, the relative bandwidth are 5 % and 4.6 %, respectively. And the isolation is better than 37 dB, which has good electrical performance.
Social Capital and Rural Health for Refugee Communities in Australia

Refugee resettlement significantly contributes to Australia’s migration programs, with recent policy directives prioritising rural resettlement. As a result, the cultural diversity of populations of several Australian rural towns has substantially expanded. Newcomers may encounter challenges becoming part of closed social networks and accessing the resources they need for a healthy life in resettlement. However, there are also benefits that stem from positive integration for newcomers and for receiving populations. As part of a larger study, which aimed to explore facilitators and barriers to successful resettlement in a rural setting, the objective of this paper was to show how social ties were important for participants’ health, both facilitating access to resources, including health services, and connecting people to health-promoting living conditions. In-depth individual interviews with 44 participants from refugee communities originally from Africa and South-East Asia, settled in a rural South Australian town, were conducted. Participants were invited to the study through snowball sampling via known connections between the researchers and key people within the communities. Interview transcripts were analysed using framework thematic analysis. The findings demonstrate how participants drew on connections within their cultural communities, reflecting collectivist cultural values. These social ties were key to enabling access to resources for health. These included emotional resources, such as a sense of belonging, as well as physical and practical resources, including food, housing, and/or accessing services. Several participants were also working towards a career in the health industry. Populations from refugee communities in rural towns are growing, not only with the continuation of new arrivals to these towns, but also as the settled populations expand their families and communities. Effective health service provision in these locations needs to serve these growing communities, and there is scope for services to tap into community networks to assist with this.
Optimal guaranteed cost control for interconnected large-scale systems under networked gossip protocol

In this note, the optimal guaranteed cost control problems for interconnected systems subject to gossip scheduling protocol are studied. For each subsystem, gossip protocol can decide the communication order of various neighbors. Each subsystem’s local controller at every instant will select only one neighboring sub-controller to transfer its subsystem’s state information. Some sufficient conditions are performed so as the closed-loop interconnected system achieves exponential stability and the cost function is less than a certain maximal value. All the distributed controller gains are designed according to the solutions of the developed linear matrix inequality conditions. Finally, the developed theoretical results are verified via the given example.
Cutoff Properties of a Circular Waveguide Loaded with Two Eccentric Dielectric Cylinders

Abstract An exact closed-form technique is employed to calculate the cutoff wavenumbers of a conducting circular waveguide loaded with two circular dielectric cylinders. An analytical expression of the hybrid modes is derived in terms of cylindrical coordinates of the geometry. The addition theorem of Bessel functions is used to transfer the electromagnetic fields from one coordinate system to another to apply the boundary conditions. A MATLAB (The MathWorks, Natick, Massachusetts, USA) code is developed to solve the system of equations and produce the cutoff wavenumbers for different geometrical parameters. The present problem can be extended to model a circular waveguide loaded with multiple dielectric cylinders that resembles a petroleum-carrying pipeline. A professional High Frequency Structure Simulator (HFSS; ANSYS, Inc., Canonsburg, PA, USA) is used to solve this model and to determine the ratio of the multi-phase fluid.
Antipodal Vivaldi Antenna with Resistance Loading on Bent Terminal

This paper presented an antipodal Vivaldi antenna with resistance loading on bent terminal. The bent terminal is composed by bidirectionally linear folded lines to prolong the effective current path, and the loaded resistors on folded lines are utilized to consume partial current energy of low frequencies. Rectangular slot edges on flared patch are also configurated. All the operations lead to remarkable improvements on low frequency performances. Simulated results show that the antenna aperture width is about $0.18\lambda 0$ at the lowest operating frequency.