In the framework of fully vertical GaN-on-Silicon device technology development, we report on the optimization of non-alloyed ohmic contacts on the N-polar n+ doped GaN face backside layer. This evaluation is made possible by using patterned TLMs (Transmission Line Model) through direct laser writing lithography after locally removing the substrate and buffer layers in order to access the n+ doped backside layer. As deposited non-alloyed metal stack on top of N-polar orientation GaN layer after buffer layers removal results in poor ohmic contact quality. To significantly reduce the related contact resistances, an HCl treatment is applied prior to metallization under various time and temperature conditions. A 3-minutes HCl treatment at 70°C is found to be the optimum condition to achieve thermally stable high ohmic contact quality. To further understand the impact of the wet treatment, SEM (Scanning Electron Microscopy) and XPS (X-ray Photoelectron Spectroscopy) analysis were performed. XPS revealed a decrease in Ga-O concentration after applying the treatment, reflecting the higher oxidation susceptibility of the N-polar face compared to the Ga-polar face, which was used as a reference. SEM images of the treated samples show the formation of pyramids on the N-face after HCl treatment, suggesting specific wet etching planes of the GaN crystal from the N-face. The size of the pyramids is time-dependent; thus, increasing the treatment duration results in larger pyramids, explaining the degradation of ohmic contact quality after prolonged high temperature HCl treatment.

Power semiconductor devices are essential from the operation point of view, size, efficiency and cost, these components are used in a myriad of applications, providing features that make them an important part of the system in which they are operating. This document analyzes and compares the basic structure, properties, design aspects, as well as temperature performance, stability and switching losses, present in devices on silicon (Si), silicon carbide (SiC) and new generation devices fabricated in gallium nitride (GaN) applied in renewable energy systems. The main objective is determinate the viability of the new generation components, which present a superior performance in view of an increase in efficiency, conductivity, decreases in switching losses, lower resistances and parasitic capacitances as well as higher operating frequency range. Therefore demonstrating the GaN components are a strong and viable candidate to solve some of the problems present in renewable energy systems.

The outdoor field test of the 4-terminal on Si tandem photovoltaic module (specifically, InGaP/GaAs on Si) was investigated and performance model, considering spectrum change affected by fluctuation of atmospheric parameters, was developed and validated. The 4-terminal on Si tandem photovoltaic module had about 40 % advantage in seasonal performance loss compared with standard InGaP/GaAs/InGaAs 2-terminal tandem photovoltaic module. This advantage is expanded in (subarctic zone) < (temperate zone) < (subtropical zone). The developed and validated model used all-climate spectrum model and considered fluctuation of atmospheric parameters, and can be applied every type of on-Si tandem solar cells.

In this work, we present an analytical model of dynamic power losses for enhancement-mode AlGaN/GaN high-electron-mobility transistor power devices (eGaN HEMTs). To build this new model, the dynamic on-resistance (Rdson) is first accurately extracted by our ex-traction circuit based on a double-diode isolation (DDI) method for a high operating frequency up to 1 MHz and a large drain voltage up to 600 V, thus the unique problem of an increase in the dynamic Rdson is presented. Then the impact of the current operation mode on the on/off transi-tion time is evaluated by a dual-pulse-current-mode test (DPCT) which including a discontinu-ous conduction mode (DCM) and a continuous conduction mode (CCM), thus the transition time is revised for different current mode. Afterward the discrepancy between the drain current and the real channel current is qualitative investigated by an external shunt capacitance (ESC) meth-od, thus the losses due to device parasitic capacitance are also taken into account. After these improvements, the dynamic model will be more compatible for eGaN HEMTs. Finally, the dynamic power losses calculated by this model are verified to be in good agreement with experimental results. Based on this model, we propose a superior solution with qua-si-resonant mode (QRM) to achieve lossless switching and accelerate switching speed.

The authors of the article performed computer simulation of buffer amplifiers (BA), which have medium and extremely small values of the offset voltage's systematic component (V_off), for different technological processes (Si, GaAs and GaN). The proposed control units are distinguished by a small number of elements and allow operation in the range of low and high temperatures. The variants of circuitry implementation of control units based on GaAs, GaN depletion-mode CMOS and JFET technological processes are considered. The results of the comparative modeling showed that the basic circuit of the BA on two field-effect transistors, when implemented on various modifications of GaN MOS and depletion-mode MOS transistors, provides sufficiently low values of the offset voltage's systematic component (less than 2 μV). The proposed BAs are designed for use in the structure of the Sallen-Key low-pass filter (LPF) when they are implemented both on mid-frequency Si CJFET and on GaAs microwave transistors. Low values of the LPF V_off have a positive effect on the effective capacity of the ADC. An example of switching on a BA in the JFET OpAmp structure based on the depletion-mode MOS input stage and a “folded” cascode, which, with 100% negative feedback, can be used in the Sallen-Key LPF, is considered. Computer simulation of the JFET/MOS OpAmp showed that the OpAmp has an open-loop voltage gain of 76-85dB, and its V_off is within 7µV in the temperature range from -60°C to +120°C. The presented circuitry of buffer amplifiers is intended, first of all, for the tasks of designing precision Sallen-Key low-pass filter (low-pass filter, high-pass filter, PF, RF).

A series of Si-bearing MgAl₂O₄-spinels were synthesized at 1500-1650 °C and 3–6 GPa. These spinels had SiO₂ contents up to ~1.03 wt%, and showed a substitution mechanism of Si⁴⁺ + Mg²⁺ = 2Al³⁺. Unpolarized Raman spectra were collected from polished single grains, and displayed a set of well-defined Raman peaks at ~610, 823, 856 and 968 cm^-1 which had not been observed before. Aided with the Raman features of natural Si-free MgAl₂O₄-spinel, synthetic Si-free MgAl₂O₄-spinel, natural low quartz, synthetic coesite, synthetic stishovite and synthetic forsterite, we infer that these Raman peaks should belong to the SiO₄ groups. The relations between the Raman intensities and SiO₂ contents of the Si-bearing MgAl₂O₄-spinels suggest that at some P-T conditions some Si must adopt the M-site. Unlike the SiO₄ groups with very intense Raman signals, the SiO₆ groups are largely Raman-inactive. We have further found that the Si cations primarily appear on the T-site at P-T conditions ≤ ~3–4 GPa and 1500 °C, but attain a random distribution between the T-site and M-site at P-T conditions ≥ ~5–6 GPa and 1630–1650 °C. This Si-disordering process observed for the Si-bearing MgAl₂O₄-spinels hints that similar Si-disordering might happen to the (Mg,Fe)₂SiO₄-spinels (ringwoodite), the major phase in the lower part of the mantle transition zone of the Earth and the index mineral for the very strong shock stage experienced by extraterrestrial materials. The likely consequences have been explored.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ~ 400 nm nano-holes in a Cr etch mask that was tens-of-nm thick. Nano-holes ablated at slightly above the threshold of ablation irradiance became nano-disks and nano-rings at slightly lower pulse energies. Subtle sub-1 nJ pulse energy control was harnessed to pattern large surface areas with controlled nano-alloying of Si and Cr. This technique is extendable to vacuum-free large area patterning of nanolayers by alloying them at distinct locations with sub-diffraction resolution. Such metal masks with nano-hole opening can be used for formation of random patterns of nano-needles with sub-100 nm separation when applied to dry etching of Si.

In the present work, diamond films have been grown on GaN-on-Sapphire substrates by chemical vapor deposition (CVD) with the addition of nitrogen to the standard H2/CH4 precursor recipe. Diamond on GaN materials processing is not straight-forward, as GaN is susceptible to a quasi-pure hydrogen CVD plasma etching. 1%, 3% and 5% N2 gas was gradually added to the H2 gas with fixed 6% CH4 in the recipe to promote the growth of diamond nanocrystals. Different types of microstructures were produced, with addition of nitrogen to the precursor gas recipe. Nitrogen gas changes the diamond film microstructure from faceted to spherical grains, with signs of GaN etching. The sp3 bonded diamond film produced by nitrogen addition was found to be co-deposited along with a considerable amount of other non-diamond carbon phases (D - disordered graphite, G - crystalline graphite, TPA - trans-polyacetylene) and qualitatively all the diamond films were 50% pure (Raman peak ratio Isp3 / ID). The FWHM of the sp3 carbon Raman peak was calculated to be 6.5 cm-1, when there was no nitrogen gas in the precursor recipe, which deteriorates to a large extent after successive addition of N2. Fourier transform infrared spectroscopy (FTIR) showed a strong presence of the nitrogen related defects (peak positions at 1190 and 1299 cm-1) inside the nanocrystalline diamond (NCD) films grown with N2 addition. GaN layer etching from the base substrate by the CVD plasma was clearly evidenced by energy dispersive X-ray spectra (EDS) of the deposited films. Al elemental EDS peaks from the base sapphire substrate were observed for the films grown with nitrogen addition, but no Ga EDS peaks were detected. X-ray diffraction (XRD) micrographs further supported the enhanced GaN etching phenomenon. Nitrogen addition was thus found to be detrimental for growing CVD diamond films over GaN surfaces. The electrical resistivity of the uncoated GaN was initially measured to be 22.2 Ω-cm. However, the resistivity rose to 1.59×106 Ω-cm after the nitrogen assisted film deposition; due to the GaN etching - thereby exposing the underlying insulating sapphire substrate.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores into cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

InGaN-based red micro light-emitting diodes (µLEDs) of different sizes prepared in this work. The red GaN epilayers were grown on a 4-inch sapphire substrate through metal organic chemical vapor deposition (MOCVD). Etching, sidewall treatment, and p- and n- contact deposition was involved in the fabrication process. Initially, the etching process would cause undesirable damages to the GaN sidewalls, which leads to an increase in leakage current. Hence, we employed KOH wet treatment to rectify the defects on the sidewalls and conducted a comparative and systematic analysis on electrical as well as optical properties. We observed that the µLEDs with a size of 5µm exhibited substantial leakage current, which was effectively mitigated by the application of KOH wet treatment. In terms of optical performance, the arrays with KOH demonstrated improved Light Output Power (LOP). Additionally, while photoelectric performance exhibited a decline with increasing current density, the devices treated with KOH consistently outperformed their counterparts in terms of optoelectronic efficiency. It is noteworthy that the optimized devices displayed enhanced photoelectric characteristics without significantly altering their original peak wavelength and FWHM. Our findings point to the elimination of surface non-radiative recombination by KOH wet treatment, thereby enhancing the performance of small-sized red µLEDs which has significant potential in realizing full-color micro-displays in near-eye projection applications.

We report the electrical properties of Al0.3Ga0.7N/GaN heterojunction field effect transistor (HFET) structures with a Ga2O3 passivation layer grown by metal-organic chemical vapor deposition (MOCVD). In this study, three different thicknesses of Ga2O3 dielectric layers were grown on Al0.3Ga0.7N/GaN structures leading to metal-oxide-semiconductor-HFET or MOSHFET structures. X-ray diffraction (XRD) showed the (¯201) orientation peaks of -Ga2O3 in the device structure. The van der Pauw and Hall measurements yield the electron density of ~ 4 x1018 cm-3 and mobility of ~770 cm2V-1s-1 in the 2-dimensional electron gas (2DEG) channel at room temperature. Capacitance-voltage (C-V) measurement for the on-state 2DEG density for the MOSHFET structure was found to be of the order of ~1.5 x1013 cm-2. The thickness of the Ga2O3 layer was inversely related to the threshold voltage and the on-state capacitance. The interface charge density between the oxide and Al0.3Ga0.7N barrier layer was found to be of the order of ~1012 cm2eV-1. The annealing at 900° C of the MOSHFET structures revealed that the Ga2O3 layer was thermally stable at high temperatures resulting in insignificant threshold voltage shifts for annealed samples with respect to as-deposited (unannealed) structures. Our results show that the MOCVD-gown Ga2O3 dielectric layers can be a strong candidate for stable high-power devices.

Due to increased energy intensive human activities resulting accelerated demand for electric power coupled with occurrence of natural disasters with increased frequency, intensity, and duration, it becomes essential to explore and advance renewable energy technology for sustainability of the society. Addressing the stated problem and providing a radical solution has been attempted in this study. To harvest the renewable energy, among variety of solar cells reported, a composite a-Si/CZTS photovoltaic devices has not yet been investigated. The calculated parameters for solar cell based on the new array of layers consisting of a-Si/CZTS are reported in this study. The variation of i) solar cell efficiency as a function of CZTS layer thickness, temperature, acceptor, and donor defect concentration; ii) variation of the open circuit current density as a function of temperature, open circuit voltage; iii) variation of open circuit voltage as a function of the thickness of the CZTS layer has been determined. There has been no reported study on a-Si/CZTS configuration-based solar cell, analysis of the parameters, and study to address the challenges imped efficiency of the photovoltaic device and the same has been discussed in this work. The value of the SnO2/a-Si/CZTS solar cells obtained from the simulation is 23.9 %.

The fabrication and characterisation of photo-anodes based on black-Si (b-Si) are presented using a photo-electrochemical cell in NaOH solution. Black-Si was fabricated by maskless dry plasma etching and was conformally coated by tens-of-nm of TiO2 using atomic layer deposition (ALD) with a top layer of CoO_x cocatalyst deposited by pulsed laser deposition (PLD). Low reflectivity R < % of Black-Si over the entire visible and near-IR (λ < 2 µm) spectral range is favourable in better absorption of light while an increased surface area facilities larger current densities. Photoelectrochemical performance of the heterostructured photoanode is discussed in terms of n-n junction between b-Si and TiO₂.

Polymer-derived ceramic (PDC) based coatings like Si-C-N and their derivatives are gaining importance day by day in N/MEMS and aerospace due to their thermos-mechanical stability and conductivity. The crystallized, amorphous, and near amorphous morphology of SiCN nanocomposite coatings based on deposition conditions requires thorough investigation for appropriate utilization as they lead to differences in mechanical properties (quantified using nanoindentation in this case). A 4-stage model was proposed based on Raman spectroscopy due to the N₂-Ar pressure variations during the deposition process of SiCN coatings by magnetron sputtering. The integral intensity of the G (graphitic), disorder (D), and tetrahedral (T) peaks namely I_G, I_D, and I_T were calculated after the deconvolution of the spectra. The sp² domain size and defect parameters were evaluated and correlated with the hardness and different bond formation involving Si, C, and N. Image analysis revealed the atomic migration involved during the growth process leading to crystallization along with the formation of voids and defects. The observations were supported by FTIR and TEM-SAED analysis. The outcomes provide a foundation causing an urge to develop similar models with further elemental additions and correlate with various physical properties.

Hypoeutectic Al-Si-Cu-Mg alloys are promising candidates for use in automobile parts. Therefore, various attempts have been made to develop alternative casting technologies to improve the mechanical properties of cast alloys. In this study, the effects of modification with different levels of strontium (Sr) on primary and eutectic silicon (Si) in hypoeutectic Al-Si-Cu-Mg alloys were investigated. Using a gravity cast process, the Sr-modified samples were prepared from melts with four levels (100, 200, 300, and 400 ppm) of Sr. In addition, the wear properties of the cast samples were studied using a block-on-ring wear-testing machine. The sizes of the primary Si phases increased with increasing Sr content in the alloys. Moreover, more finely dispersed eutectic Si was observed with higher Sr content. In frictional wear tests, the specific wear rates of the test specimens decreased as the Sr content increased from 200 to 400 ppm. Coarse Si phases are considered to act as solid lubricants in the contact region during sliding.

We investigate the ammonium removal abilities of natural and synthetic zeolites, which have distinct Si/Al ratios and various surface areas, to study how adsorption and ion-exchange processes in zeolites perform under different ammonium concentrations and different temperatures. Five zeolites including natural mordenite, chabazite, erionite, clinoptilolite and synthetic merlinoite were immersed in 20 mg/kg, 50 mg/kg and 100 mg/kg ammonium solutions. The results demonstrate that zeolites under high ammonium concentrations (100 mg/kg) possess higher physical adsorption capacity (0.398–0.468 meq/g), whereas those under lower ammonium concentrations (20 mg/kg) possess greater ion-exchange property (64–99%). The ion-exchange ability of zeolites are extremely dependent on the cation content of the zeolites, and the cation content is affected by the Si/Al ratio. The surface area of zeolites also has a partial influence on its physical adsorption ability. When the surface area is less than 100 m²/g, the adsorption ability of zeolite increases obviously with surface area; however, adsorption ability is saturated as the surface area becomes larger than this critical value of 100 m²/g. When we carried out the zeolites in 50 mg/kg ammonium concentration at different temperatures (5~50 ℃), we found that zeolites exhibit the highest ammonium removal ability at 30°C and the potassium release was enhanced at 30~40 ℃.

A high-performance broadband High Power Amplifier (HPA) has been developed employing 250 nm gate length Gallium Nitride (GaN) technology from the \href{https://www.leonardo.com/en/innovation-technology/technological-areas/electronics}{LEONARDO} foundry GN25. This HPA employs the a corporate configuration for FET transistors, optimizing its performance. This article provides an in-depth study and analysis of the critical design parameters of such HPAs in Monolithic Microwave Integrated Circuit (MMIC) technology. The designed MMIC chip measures 7.5 x 7 mm^2 and includes three stages, each carefully optimized to maximize efficiency and performance. Both the design and the measurement results of amplifier are presented. he most remarkable feature of this chip is an operational bandwidth exceeding two octaves, covering a wide RF frequency range from 2 to 10 GHz (2.23:1 ratio. Additionally, the amplifier achieves an output power higher than 43 dBm, along with a power-added efficiency(PAE) surpassing 20% in the mentioned frequency range (2-10 GHz). This HPA is suitable to be integrated into future Transmit and Receive Modules (TRMs) for Active Electronically Scanned Array (AESA) systems. These systems include multiple capabilities in a single device, such as Radar, Electronic Warfare (EW), and Communications (COMMs) functions, demonstrating the versatility and high efficiency of this design in advanced multifunctional applications

Traditional image steganography conceals secret messages into unprocessed natural images by modifying the pixel value, causing the obtained stego different from the original image in terms of statistical distribution, thereby could be detected by a well-trained classifier for steganalysis. To ensure the steganography is imperceptible and in line with the trend of art images produced by Artificial Intelligence Generated Content (AIGC) becoming popular in social networks, this paper proposes to embed hidden information throughout the process of the generation of an art-style image by designing an image style transformation neural network with steganography function. The proposed scheme takes a content image, an art-style image, and messages to be embedded as inputs, processing them with an encoder-decoder model, and finally generates a styled image containing the secret messages at the same time. An adversarial training technique is applied to enhance the imperceptibility of the generated art-styled stego image with from plain style-transferred images. The lack of the original cover image makes it difficult for the opponent learning a steganalyzer to identify the stego. The recommended approach can successfully withstand existing steganalysis techniques and attain the embedding capacity of 3 bits per pixel for a color image, according to experimental results.

Active magnetic bearings have higher efficiency than other bearings because there is no physical contact. However, this benefit is mitigated by the addition of electrical power consumption. It is therefore important for magnetic bearings to have efficient power electronics. Gallium nitride-based transistors are a relatively new form of transistor which have shown to be more efficient than MOSFETs. There is an insufficient body of literature in the area of application of these transistors for magnetic levitation. This work presents a simple 1 degree-of-freedom voltage controlled levitation experiment in which levitation is achieved with both a gallium nitride transistor and a MOSFET.
Voltage losses and current consumption are measured when using each transistor during levitation. In particular, transients during open-to-closed and closed-to-open states are measured for PWM pulsing. It is found that the
gallium nitride transistor is superior in both switching time and efficiency in situ for magnetic levitation.

We present TOLGAN that generates traditional oriental landscape (TOL) image from a map that specifies the locations and shapes of the elements composing TOL. Users can create a TOL map by using a user interface or a segmentation scheme from a photograph. We design the generator of TOLGAN as a series of decoding layers where the map is applied between the layers. The generated TOL image is further enhanced through an AdaIN architecture. The discriminator of TOLGAN processes a generated image and its groundtruth TOL artwork image. TOLGAN is trained through a dataset composed of paired TOL artwork images and their TOL maps. We present a tool through which users can produce a TOL map by specifying and organizing the elements of TOL artworks. TOLGAN successfully generates a series of TOL images from the TOL map. We evaluate our approach using a quantitative way by estimating FID and ArtFID scores and a qualitative way by executing two user studies. Through these studies, we prove the excellence of our approach by comparing our results with those from several important existing works.

Recent advances in deep learning technology have led to increased interest in text-to-image technology, which enables computers to create images from text by simulating the human process of forming mental images. The GAN-based text-to-image technology involves the extraction of features from input text, which are combined with noise and then used as input to a GAN that generates images that are similar to the original images through competition between the generator and discriminator. Although generating images from English text is a mature area of research, text-to-image technology based on multilingualism, such as Korean, is still in its early stages of development. Webtoon is a digital comic format that allows comics to be viewed online. The creation process for webtoons is divided into story planning, content/sketching, coloring, and background drawing. Since each stage of webtoon production requires human intervention, it is both time-consuming and expensive. As a result, deep learning technologies such as automatic coloring and automatic line drawing are being used to reduce human involvement. However, there is a shortage of technology that can assist authors with story creation in webtoon production. Therefore, this study proposes a multilingual text-to-image model capable of generating webtoon images when presented with multilingual input text. The proposed model employs Multilingual BERT to extract feature vectors for multiple languages, and trains a DCGAN in conjunction with the images. The experimental results demonstrate that the model can generate images that are similar to the original images when presented with multilingual input text after training.

The effect of growth temperature and precursor flows on the doping level and surface morphology of Ge-doped GaN layers was researched. The results show that germanium is more readily incorporated at low temperature, high growth rate and high V/III ratio, thus revealing a similar behavior to what was previously observed for indium. V-pit formation can be blocked at high temperature but also at low V/III ratio, the latter of which however causing step bunching.

In personalized healthcare, an ecosystem for the manipulation of reliable and safe private data should be orchestrated. This paper describes a first approach for the generation of fake electrocardiograms (ECGs) based on Generative Adversarial Networks (GANs) with the objective of anonymizing users’ information for privacy issues. This is intended to create valuable data that can be used both, in educational and research areas, while avoiding the risk of a sensitive data leakage. As GANs are mainly exploited on images and video frames, we are proposing general raw data processing after transformation into an image, so it can be managed through a GAN, then decoded back to the original data domain. The feasibility of our transformation and processing hypothesis is primarily demonstrated. Next, from the proposed procedure, main drawbacks for each step in the procedure are addressed for the particular case of ECGs. Hence, a novel research pathway on health data anonymization using GANs is opened and further straightforward developments are expected.

In this paper, our goal is to perform a virtual restoration of an ancient coin from its image. The present work is the first one to propose this problem, and it is motivated by two key promising applications. The first of these emerges from the recently recognised dependence of automatic image based coin type matching on the condition of the imaged coins; the algorithm introduced herein could be used as a pre-processing step, aimed at overcoming the aforementioned weakness. The second application concerns the utility both to professional and hobby numismatists of being able to visualise and study an ancient coin in a state closer to its original (minted) appearance. To address the conceptual problem at hand, we introduce a framework which comprises a deep learning based method using Generative Adversarial Networks, capable of learning the range of appearance variation of different semantic elements artistically depicted on coins, and a complementary algorithm used to collect, correctly label, and prepare for processing a large numbers of images (here 100,000) of ancient coins needed to facilitate the training of the aforementioned learning method. Empirical evaluation performed on a withheld subset of the data demonstrates extremely promising performance of the proposed methodology and shows that our algorithm correctly learns the spectra of appearance variation across different semantic elements, and despite the enormous variability present reconstructs the missing (damaged) detail while matching the surrounding semantic content and artistic style.

Hip replacement has significantly improved the quality of life of patients with symptomatic hip osteoarthritis. Metal-on-metal (MoM) bearings have been used with conventional total hip re-placement (THR) for several decades with promising results from early applications. Wear and corrosion of these implants may lead to a release of metal products into surrounding tissue and body fluids. From the 1980s onwards, the search for increasingly better coupling materials with low levels of wear led to the rise of hard-on-hard couplings such as ceramic-on-ceramic (CoC). The latter is currently the coupling with the longest known duration and with a wear rate close to zero. MoM coupling has been for a long time the most significative alternative, but systemic and local complications linked to the release of chromium and cobalt ions, determine the withdrawn from the market. One other alternative proposed over the time has been Ceramic-on-Metal (CoM) bearing. Preliminary results have been described as favourable, but due to the failures of metal on metal it has been withdrawn from the market, without causing significant clinical complications. In this narrative review, we analysed risks and benefits associated with the implantation of hybrid hard-on-hard bearings, such as CoM.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

In addressing the challenges of data scarcity in biometrics, this study explores the generation of synthetic palmprint images as an efficient, cost effective, and privacy preserving alternative to real-world data reliance. Traditional methods for synthetic biometric image creation primarily involve orientation modifications and filter applications, with no established method specific to palmprints. We introduced the utilization of the “Style-based generator”, StyleGAN2-ADA, from the StyleGAN series, renowned for generating high-quality images. Furthermore, we explore the capabilities of its successor, StyleGAN3, which boasts enhanced image generation, facilitating smooth and realistic transitions. By comparing the performance of StyleGAN3 on public dataset, we aim to establish the most efficient generative model for this purpose. Evaluations were conducted using the SIFT (Scale-Invariant Feature Transform) algorithm into our evaluation framework. Preliminary findings suggest that StyleGAN3 offers superior generative capabilities, enhancing equivariance in synthetic palmprint generation.

We present the results of a twofold experimental and computational study of (0001) GaN/AlN multilayers forming pseudomorphic superlattices. High-Resolution Transmission Electron Microscopy (HRTEM) shows that heterostructures with GaN Quantum Wells (QW) four c-lattice parameters thick are misfit-dislocation free. Accurate structural data are extracted from HRTEM images via a new methodology optimizing the residual elastic energy stored in the samples. Total energy calculations are performed with several models analogous to the experimental QWs with increasing thicknesses of GaN, whereas this of the AlN barrier is kept fixed at n=8 c-lattice parameters. With vanishing external stresses, minimum energy configurations of the studied systems correspond to different strain states. Linear elasticity accurately yields the corresponding lattice parameters, suppressing the need for on-purpose total energy calculations. Theoretically justified parabolic fits of the excess interfacial energy yield the values of interfacial stress and elastic stiffness as functions of the GaN QW thickness. Total species-projected densities of states and gap values extracted therefrom allow deciphering the effect of the evolving strain on the electronic structure of the superlattice. It is found that the gap energy decreases linearly with increasing the strain of the QW. These results are briefly discussed in the light shed by previous works from the literature.

GaN-based micro-size light-emitting diodes (µLEDs) have a number of appealing and distinctive benefits for display, visible-light communication (VLC), and other novel applications. The smaller size of LEDs affords them the benefits of enhanced current expansion, less self-heating effects, and higher current density bearing capacity. Low external quantum efficiency (EQE) resulting from non-radiative recombination and quantum confined stark effect (QCSE) is the serious barrier for applications of µLEDs. In this work, the reasons for the poor EQE of µLEDs are reviewed, as well as the optimization techniques for improving the EQE of µLEDs.

Recently, generative adversarial networks (GANs) can be used to generate the photo-realistic image from a low-dimension random noise. It is very dangerous that the synthesized or generated image is used on inappropriate contents in social media network. In order to successfully detect such fake image, an effective and efficient image forgery detector is desired. However, conventional image forgery detectors are failed to recognize the synthesized or generated images by using GAN-based generator since they are all generated but manipulation from the source. Therefore, we propose a deep learning-based approach to detect the fake image by combining the contrastive loss. First, several state-of-the-art GANs will be collected to generate the fake-real image pairs. Then, the contrastive will be used on the proposed common fake feature network (CFFN)to learn the discriminative feature between the fake image and real image (i.e., paired information). Finally, a smaller network will be concatenated to the CFFN to determine whether the feature of the input image is fake or real. Experimental results demonstrated that the proposed method significantly outperforms other state-of-the-art fake image detectors.

Currently, conventional spark-ignition engines face challenges in meeting the ever-growing demands of customers and increasingly stringent regulations regarding pollutant emissions. A combination of innovative strategies and carbon-neutral fuels is deemed necessary in order to further reduce fuel consumption and minimize engine emissions. The present work aims to assess the performance of combustion strategies using low-carbon content fuel, such as methanol M100, ignited by a plasma-assisted igniter (PAI) under ultra-lean conditions. The experimental campaign is conducted on a single-cylinder research engine at different engine speeds and low loads, moving up to the engine lean stable limits. To determine the benefits brought by the proposed strategy, referred to as M100-PAI, the obtained outcomes are compared with the ones obtained using market gasoline E5 ignited by the PAI system and conventional spark. The synergy between M100 (methanol) and Plasma Assisted Ignition (PAI) in internal combustion engines yielded notable benefits. This combination significantly improved combustion stability if compared to the other combinations tested, by extending the lean stable limit to λ=2.0, reducing cycle-to-cycle variability, and facilitating faster flame front acceleration, resulting in enhanced homogeneity. These enhancements, obtained with the combination M100-PAI, contributed to higher fuel efficiency showing a 10% efficiency gain over the combination E5-gasoline spark ignition.

Hydrogen fuel is gaining particular attention in internal combustion engines. In addition to zero-carbon emissions, major advantages relate to its combustion characteristics, which allow significant increase in thermal efficiency under ultra-lean operation and with very low NOx levels. The ignition system is one of the main technology enablers, as it determines the capability to control ultra-lean operations, avoid backfire phenomena, or reduce the risks of abnormal combustions. The latter results from the hydrogen low ignition energy and it is associated with factors like high-temperature residuals, hot spots, and irregular spark plug discharge. ACIS gen 2-Barrier Discharge Igniter excels in accelerating the initial flame growth speed by the generation of non-equilibrium low-temperature plasma, strong ignition promoter for the combined action of kinetic and thermal effects. Moreover, its volumetric discharge facilitates combustion initiation on a wide region, in contrast to the localized ignition of traditional spark systems. In this work we present for the first time, to the best of our knowledge, experimental results showing the performance of a hydrogen engine with a low-temperature plasma discharge. Tests were conducted on a single-cylinder research engine, achieving ultra-lean conditions with cycle-to-cycle variability results below 2.5%. The analysis indicates that the H2 - BDI combined solution is capable of accelerating the evolution of the flame front compared to traditional spark plugs, leading to a significant reduction in the cycle-to-cycle variability. A meticulous adjustment of the BDI control parameters further enhances igniter performance and contributes to a deeper understanding of the innovative approach proposed in this study.

The principal main of this research work was the study the influence of Cu addition on the wear behavior (WB) of eutectic Al-12.6Si alloy developed by spray forming (SF) method and compared with as-cast (AC) alloys. The phases of chemical compositions and microstructure were studied by optical microscopy, energy dispersive spectroscopy (EDS) and Scanning Electron Microscopy (SEM). The microstructure of SFAl-12.6Si (SF1) alloy reside — of fine primary and eutectic Si phases evenly distributed in the equiaxed α-Al matrix and SF Al-12.6Si-2Cu (SF2) alloy lie of uniformly distributed fine eutectic Si particulates and spherical form θ-Al2Cu precipitates in α-Al matrix. On other hand, the AC Al-12.6Si alloy (AC1) alloy involve of eutectic Si needles in the dendrite α-Al matrix, whereas AC Al-12.6Si-2Cu (AC2) alloy consisted of eutectic Si needles and Chinese script form θ phase distributed randomly in the α-Al matrix. The microhardness and wear properties were analyzed using Vickers hardness (VH) and dry sliding WT. The SF alloys exhibit superior hardness compared to the AC alloys. The wear properties of SF alloys exhibited significantly superior compared to the AC alloys. The SF2 alloy showed high wear resistance (WR) than the SF1 alloy in the entire sliding velocities and applied loads. The results indicate that the spray deposited alloys have a lower coefficient of friction (CF(µ)) than the AC alloys under varying load and sliding velocity conditions. The high WR in the SF alloy was due to microstructural modification during SF and precipitation of fine Al2Cu intermetallic and solid solubility effects. The SF2 depicts increased transition from oxidative to abrasive. In other ways, AC alloys demonstrate wear mechanisms that change from oxidative to abrasive and delamination with an increase in sliding velocity and load.

Thermal analysis of a hypereutectic Al-Si alloy used for an automotive part was carried out in this research work. Solidification characteristics are recognized from the Temperature-time curve and its corresponding derivatives. This analysis was successfully used in a simulation software program with the aim of improving the resultant simulation accuracy. In this study, different types of molds, with and without cooling systems, were designed and used. The melt present in the furnaces of the factory was used to simulate the casting process. The effect of different cooling rates (1.2ºC/s, 2ºC/s, 2.3ºC/s and 2.9ºC/s) on the solidification parameters have been investigated. Differences in the resultant microstructure between wall and center of the molds have been analyzed and have been related to the T-t curve. Finally, the experimental results clearly indicate that the water-cooling rate of the molds and the melt temperature directly affects the solidification process as well as the final microstructure.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ~ 0.4 − 1 μm holes in alumina Al2O3 etch masks with 20-50 nm thickness. Such dielectric masks simplify fabrication of photonic crystal (PhC) light trapping patterns for the above-Lambertian performance of high efficiency solar cells. Conditions of laser ablation of transparent etch masks and effects sub-surface Si modifications were revealed by plasma etch- ing, numerical modeling, and minority carrier lifetime measurements. Mask-less patterning of Si is proposed using fs-laser direct writing for dry plasma etch of Si.

The synergistic effect of silicon and cerium addition on the oxidation resistance of pack cementation aluminide coating applied on Ni-based superalloy substrate was investigated. The effect of cerium and silicon on the scale morphology, oxidation behavior, and scale spallation tendency are discussed based on the experimental results, using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray analyses (EDX). In addition, the oxidation resistance was evaluated by measuring the weight of samples after each 16-hour cycle at 1100˚C for 50 cycles. The experiments indicated that silicon addition to aluminide coating improves the oxidation resistance through the formation of β-NiAl1-nSin and δ-Ni2Al3-nSin and δ-Ni2Si phases. Furthermore, the addition of 1% cerium to modified aluminide enhances the formation of the fine-grained microstructure of the β-NiAl and δ-Ni2Al3 and reduces the outward/inward diffusion of elements (so-called blocking effect) which significantly modifies the hot oxidation resistance. The addition of 2% cerium, owing to the distortion of the β-NiAl and δ-Ni2Al3 phases, strictly decreases the hot oxidation resistance and the coating is exfoliated after 450 h at 1100 °C. The cyclic oxidation tests showed that the samples containing 1% cerium and 6% silicon possess the highest hot oxidation resistance in which 2 mg/cm2 weight loss of Ce-Si-aluminide was reported after 800 h. This is attributed to the simultaneous effect of cerium and silicon during the deposition process which reduces the oxygen diffusion and reduces the growth rate of α-Al2O3 during oxidation tests. The α-Al2O3 oxidation layer morphology showed that finer grains are formed in samples containing optimum ratios of cerium and silicon which indicates that these elements improve the coating adhesion and oxidation resistance simultaneously.

The corrosion behavior of Fe-containing directionally solidified (DS) and centrifugally cast (CC) Al-Si-Cu-Zn alloys with either Co or Ni additions has been investigated. Electrochemical and immersion corrosion methods were used to investigate the corrosion behavior in 0.6 M NaCl after short (1-hour) and long (30-day) exposure periods. The employed solidification methods allowed the production of samples with a wide range of secondary dendrite arm spacing (SDAS) while preserving Si and Fe-containing phases. The 0.5 wt.% Ni and Co additions led to the growth of the AlFeSi(Ni) and AlFeSi(Co) phases, but no binary AlNi nor AlCo intermetallic par-ticles have been generated. Potentiodynamic polarization studies at early exposure revealed an increase in the corrosion potential as the Ni was added for either fast or slow solidified samples. The electrochemical impedance spectroscopy at early exposure demonstrated that the Ni-modified alloy, on the other hand, was associated to smaller charge transfer resistances, in-dicating a reduction in corrosion resistance after short elapsed time into the electrolyte. Howev-er, 30-day immersion tests revealed much lower corrosion rate of the Ni-modified alloy than the other alloys, while the corrosion rates of the Co-modified and non-modified alloys were simi-lar. In the Ni-containing alloy, decreased corrosion rate under long-term corrosion process was attributed to the formation of a thick and dense alumina layer, effectively protecting the surface under such conditions. This work contributes to a better knowledge of the corrosion behavior of Ni- and Co-corrected Al industrial scrap compositions.

We report the effects of surface passivation by depositing a hydrogenated amorphous silicon (a-Si:H) layer on the electrical characteristics of low temperature polycrystalline silicon thin film transistors (LTPS TFTs). The a-Si:H layer was optimized by hydrogen dilution and its structural and electrical characteristics were investigated. The a-Si:H layer in the transition region between a-Si:H and µc-Si:H resulted in superior device characteristics. Using an a-Si:H passivation layer, the field-effect mobility of the LTPS TFT was increased by 78.4% compared with a conventional LTPS TFT. Moreover, the leakage current measured at a V_GS of 5 V was suppressed because the defect sites at the poly-Si grain boundaries were well passivated. Our passivation layer, which allows thorough control of the crystallinity and passivation-quality, should be considered a candidate for high performance LTPS TFTs.

Alzheimer’s disease (AD) is a significant health concern worldwide with enormous social and economic impact globally. The gradual deterioration of cognitive functions and irreversible neuronal losses are primary features of the disease. Even after decades of research, most therapeutic options are merely symptomatic, and drugs in clinical practice present numerous side effects. Lack of effective diagnostic techniques prevents the early prognosis of disease, resulting in a gradual deterioration in the quality of life. Furthermore, the mechanism of cognitive impairment and AD pathophysiology is poorly understood. Microfluidics exploits different microscale properties of fluids to mimic environments on microfluidic chip-like devices. These miniature multichambered devices can be used to grow cells and 3D tissues in vitro, analyze cell-to-cell communication, decipher the roles of neural cells like microglia, and gain insights into AD pathophysiology. This review focuses on the applications and impact of microfluidics on AD research. We discuss the technical challenges and possible solutions provided by this new cutting-edge technique to understand disease-associated pathways and mechanisms.

Purposes: To provide abdominal contrast-enhanced MR image synthesis, we developed an image gradient regularized multi-modal multi-discrimination sparse-attention fusion generative adversarial network (GRMM-GAN) to avoid repeated contrast injections to patients and facilitate adaptive monitoring. Methods: With IRB approval, 165 abdominal MR studies from 61 liver cancer patients were retrospectively solicited from our institutional database. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast-enhanced (T1ce) images. The GRMM-GAN synthesis pipeline consists of a sparse attention fusion network, an image gradient regularizer (GR), and a generative adversarial network with multi-discrimination. The studies were randomly divided into 115 for training, 20 for validation, and 30 for testing. The two pre-contrast MR modalities, T2 and T1pre images, were adopted as inputs in the training phase. The T1ce image at the portal venous phase was used as an output. The synthesized T1ce images were compared with the ground truth T1ce images. The evaluation metrics include peak signal-to-noise ratio (PSNR), structural-similarity-index (SSIM), and mean-squared-error (MSE). A Turing test and experts’ contours evaluated the image synthesis quality. Results: The proposed GRMM-GAN model achieved a PSNR of 28.56, an SSIM of 0.869, and an MSE of 83.27. The proposed model showed statistically significant improvements in all metrics tested with p-values <0.05 over the state-of-the-art model comparisons. The average Turing test score was 52.33%, close to random guessing, supporting the model's effectiveness for clinical application. In the tumor-specific region analysis, the average tumor contrast-to-noise ratio (CNR) of the synthesized MR images was not statistically significant from the real MR images. The average DICE from real vs. synthetic images was 0.90, compared to the inter-operator DICE of 0.91. Conclusion: We demonstrated the function of a novel multi-modal MR image synthesis neural network, GRMM-GAN, for T1ce MR synthesis based on pre-contrast T1 and T2 MR images. GRMM-GAN shows promise for avoiding repeated contrast injections during radiation therapy treatment.

This research aims to investigate and conduct the impact of earnings management practices on the performance of the banking sector in Jordan. Data were collected from 24 main commercial banks from (2015 – 2021). The study examine how earnings management practices affect banking sector performance using debt ratios and equity ratios based on firm size and debt ratios, and measure the impact of earnings management on it using regression analysis. The result of the study reveal that a positive and statistically significant association between equity per share (EPS) and return on investment (ROI) with earnings management practices, also, earnings management techniques are positively and significantly impacted by return on equity (ROE), the hypothesis that returns on investment (ROI) encourage business managers to employ earnings management strategies. Also, the study show that dependent variables of earnings management is measured as a debt ratio and equity ratio. Variables that are independent or explanatory of earnings management are considered independent variables.

Background: Exclusively breastfeeding your newborn while in the hospital is imperative for suc-cessful breastfeeding at home. This study will investigate if having a nurse on-site during rooming-in can enhance the proportion of exclusive breastfeeding. Methods: We carried out a prospective cohort study to assess exclusive breastfeeding in the first three months of life among two Neona-tology Units in Southern Italy with different hospital settings. The Ente Ecclesiastico Miulli of Ac-quaviva delle Fonti had on-site nurses available 24/7 (on-site group), while the Policlinico of Bari had nurses available on call 24/7 from the Neonatology Unit (on-call group). Results: Between January 3rd and March 31st, 2018, a total of 564 sets of mothers and babies were admitted - 299 on-site and 265 on-call. The exclusive breastfeeding rate for the entire group was 76.4% at 90 days, demonstrating the positive impact of rooming-in and nursing, regardless of the setting. Infants delivered via ce-sarean section in the on-site group demonstrated higher rates of exclusive breastfeeding at both 30 and 90 days of life. Conclusions: Our research indicates that having a nurse available at all times is crucial for promptly identifying any problems with breastfeeding. We highly suggest having an on-site nurse present during rooming-in for mothers who have had a caesarean delivery. This nurse should continuously promote exclusive breastfeeding until the baby is three months old.

Microfluidic lab-on-chip devices are widely being developed for chemical and biological studies. One of the most commonly used types of these chips is perfusion microwells for culturing multicellular spheroids. The main challenge in such systems is the formation of substantial necrotic and hypoxic zones within the cultured spheroids. Herein, we propose a novel acoustofluidic integrated platform to tackle this bottleneck problem. We show that such an approach enhances cell viability and shrinks necrotic and hypoxic zones in these spheroid-on-a-chip platforms without the need to increase the flow rate, leading to a significant reduction in costly reagents' consumption. Proof-of-concept, designing procedures, and finite element numerical simulation are discussed in details. Also, the effects of acoustic and hydrodynamic parameters on the cultured cells are investigated. The results show that by increasing acoustic boundary displacement amplitude (d0), the spheroid’s proliferating zone enlarges greatly. Moreover, it is shown that by implementing d0=0.5 nm, the required flow rate to maintain the necrotic zone below 13% will be decreased 12 times compared to non-acoustic chips.

The Yb/Al multilayer films exhibit excellent theoretical reflectivity in the 54-90nm wavelength range. This study attempted to incorporate 1.5% wt.% of Si impurities into Al to suppress the crystallization of Al, reduce interfacial roughness, and enhance the actual reflectivity of the prepared Yb/Al multilayer films. The internal microstructure changes of the film layers before and after Si impurity doping were investigated using GIXRR, AFM, and XRD techniques. The reflectivity of two types of multilayer films, Yb/Al(1.5wt.%Si) and Yb/Al(pure), was tested to evaluate the effect of Si impurity on the film performance.

The possibility of using Si-based anodes in lithium-ion batteries is actively investigated due to the increased lithium capacity of silicon. The paper reports the preparation of submicron silicon fibers on glassy carbon in the KI–KF–KCl–K2SiF6 melt at 720°C. For this purpose, the parameters of silicon electrodeposition in the form of fibers were determined by cyclic voltammetry, and ex-perimental samples of ordered silicon fibers with an average diameter from 0.1 to 0.3 μm were obtained under galvanostatic electrolysis conditions. Using the obtained silicon fibers, anode half-cells of lithium-ion battery was fabricated, and its electrochemical performance under mul-tiple lithiation and delithiation was studied. By means of voltametric studies, it is observed that charging and discharging of the anode based on the obtained silicon fibers occurs at potentials from 0.2 to 0.05 V and from 0.2 to 0.5 V, respectively. A change in discharge capacity from 520 to 200 mAh g-1 during the first 50 charge/discharge cycles at a charge current of 0.1C and a Coulomb ef-ficiency of 98-100% was shown. The possibility of charging silicon-based anode samples at charging currents up to 2C was also noted; the discharge capacity ranged from 25 to 250 mAh g-1.

The cast defects strongly degrade the mechanical properties in cast alloys. The effect of Sn addition on Al-Si alloys was investigated by 3D computed tomography, SEM and TEM. Amorphous Sn oxides are found near the alumina film, cause more shrinkage pores, initiate cracks and deteriorate mechanical properties. This work suggests not adding Sn in various Al alloys used in cast state.

Silicon has a theoretical specific capacity of 4200 mAh g−1, which is considered to have significant potential for anode materials in lithium-ion batteries (LIBs). However, the volume change that occurs in silicon during charging and discharging affects the development of commercial applications. In this work, a yolk-shell structured Si@void@C anode material has been developed to address this problem. The silicon nanoparticle yolk material is obtained by recycling kerf-loss (KL) Si waste from the photovoltaic industry, the carbon shell is prepared via a hydrothermal process with glucose, and the sacrificial interlayer is Al2O3. The synthesized material is used to fabricate anodes that show a high reversible capacity of 836 mAh g−1 at the current density of 0.1 A g−1 after 100 cycles, with a Coulomb efficiency of 71.4%. This work demonstrates a relatively low-cost approach to turn KL Si waste into value-added materials for LIBs.

The design of processing routes involving the presence of the liquid phase is mainly associated with the knowledge of its surface and transport properties. Despite this need, due to experimental difficulties related to high temperature measurements of metallic melts, for many alloy systems neither thermodynamic nor thermophysical properties data are available. A good example lacking these datasets represents the Ir-Si system, although over the last fifty years, the structures and properties of its solid phases have been widely investigated. To compensate the missing data, the Gibbs free energy of mixing of the Ir-Si liquid phase was calculated combining the model predicted values for the enthalpy and entropy of mixing using Miedema’s model and Free Volume Theory, respectively. Subsequently, in the framework of statistical mechanics and thermodynamics, the surface properties were calculated using the Quasi Chemical Approximation (QCA) for the regular solution, while to obtain the viscosity, the Moelwyn-Hughes (MH) and Terzieff models were applied. Subsequently, the predicted values of the abovementioned thermophysical properties were used to model the non-reactive infiltration isotherm of Ir-Si (eutectic) / SiC system.

Traditional refractory materials such as nickel-based superalloys have been gradually unable to meet the performance requirements of advanced materials. The Mo-Si-based alloy, as a new type of high temperature structural material, has entered the vision of researchers due to its charming high temperature performance characteristics. However, its easy oxidation and even "pesting oxidation" at medium temperatures limit its further applications. In order to solve this problem, researchers have conducted large numbers of experiments and made breakthrough achievements. Based on these research results, the effects of rare earth elements like La, Hf, Ce and Y on the microstructure and oxidation behavior of Mo-Si-based alloys were systematically reviewed in the current work. Meanwhile, this paper also provided an analysis about the strengthening mechanism of rare earth elements on the oxidation behavior for Mo-Si-based alloys after discussing the oxidation process. Furthermore, the research focus about the oxidation protection of Mo-Si-based alloys in the future was prospected to expand the application field.

Cylindrical Fe-6.5wt.% Si bars with 7.5 mm in diameter were successfully fabricated from as cast ingot through three rolling stages within 10 passes: rough rolling at 850–900 °C and 8–10 m/min, medium rolling at 800–850 °C and 10–15 m/min, and finish rolling at 800–850 °C and 12–18 m/min. The evolution of microstructure, texture and ordered structure, and the mechanical property are investigated. The results showed that the grains were refined by the hot bar rolling. Area fractions of the {100}<011> oriented grains and the {011}<100> oriented grains decreased to 0 during the hot bar rolling. Whereas, the {100}<001> component, the {011}<211> component and the {112}<110> component increased, and γ fiber with {111}<110> component was dominant. DO₃ ordered phase were suppressed, and B2 ordered domains were refined after the hot bar rolling. Ductility of the as rolled bar was higher than that of the rotary swaged bar, due to the absence of the DO₃ ordered phase and the fine grains in the rolled bar. Hence, the hot bar rolling technology is an excellent process to fabricate the Fe-6.5wt.% Si bars.

Generative artificial intelligence (GenAI) has been developing with many incredible achievements like ChatGPT and Bard. Deep generative model (DGM) is a branch of GenAI, which is preeminent in generating raster data such as image and sound due to strong points of deep neural network (DNN) in inference and recognition. The built-in inference mechanism of DNN, which simulates and aims to synaptic plasticity of human neuron network, fosters generation ability of DGM which produces surprised results with support of statistical flexibility. Two popular approaches in DGM are Variational Autoencoders (VAE) and Generative Adversarial Network (GAN). Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. In this research, VAE and GAN is unified into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is good at generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. In other words, AVA aims to improve accuracy of generative models, besides AVA extends function of simple generative models. In methodology this research focuses on combination of applied mathematical concepts and skillful techniques of computer programming in order to implement and solve complicated problems as simply as possible.

This paper presents a 32 GHz high power amplifier (HPA) with a design strategy to achieve a high-power output with reliable operation for the Ka-band deep space satellite communication in 150 nm GaN HEMT technology. The presented Ka-band HPA employs a cascaded two-stage common source amplifier topology, and the output stage is comprised of an 8-way power combining network in current mode. The interstage matching network is designed with the bandpass configuration utilizing capacitors and transmission lines to provide better stability at the low-frequency regime. The implemented Ka-band HPA achieved a peak power gain of 7.3 dB at 32 GHz and a 3 dB bandwidth was 3.5 GHz between 31.3 and 34.8 GHz. The saturated output power at the peak power added efficiency (PAE) of 19.3% was 38.2 dBm, and the output 1 dB gain compression point (OP1dB) was 27.4 dBm in the measurement. The designed HPA consumes an area of 19.35 mm^2 including RF signal, and DC pads

The development of sensors for monitoring Carbon Monoxide (CO) in a large range of temperature is of crucial importance in areas as monitoring of industrial processes or personal tracking using smart objects. Devices integrating GaN/Ga₂O₃ core/shell nanowires (NWs) is a promising solution allowing combining the high sensitivity of the electronic properties to the states of GaN-core surface; and the high sensitivity to CO of Ga₂O₃-shell. Because the performances of sensors primarily depend on the material properties composing the active layer of the device, it is essential to control these properties and in first time its synthesis. In this work, we investigate the synthesis of GaN/Ga₂O₃ core-shell NWs with a special focus on the formation of the shell. The GaN NWs grown by Plasma-assisted molecular beam epitaxy, are post-treated following thermal oxidation to form Ga₂O₃-shell surrounding the GaN-core. We establish that the Ga₂O₃-shell thickness can be modulated from 1 up to 14 nm by changing the oxidation conditions, and follows the diffuse-controlled reaction. By combining XRD-STEM and EDX analysis, we also demonstrate that the oxide shell formed by thermal oxidation is crystalline and presents the β-Ga₂O₃ crystalline phase, and is synthesized in epitaxial relationship with the GaN-core.

Pin-on-plate and pin-on-disk wear tests are typically used for assessing the wear behavior of a given material coupling. Such a behavior is frequently described by a wear coefficient k, which is estimated, according to the Archard’s law, as the ratio between the measured wear volume V and the product of the applied normal force F and the sliding distance s, i.e. k=V/(F s). This study demonstrates that such a relationship is correct for pin-on-plate but not for pin-on-disk, particularly for flat-ended pins. Both analytical and finite element models of the two tests were developed, considering three different distances pin-disk axis. As results, wear volumes, pressure and wear depth maps were examined and compared for the same sliding distance. Though this study is focused only on the initial transient part of the wear tests, some interesting aspects arose: i) rotational effect in pin-on-disk tests affects k estimation, especially when the pin is near to the disk axis; ii) a simple analytical function is defined to correct the wear volume estimation for pin-on-disk tests; iii) due to the different sliding distances of contact points in pin-on-disk tests, pressure redistribution occurs with higher values on the inner side (closer to disk axis); the opposite trend is observed in wear depth maps. From a computational point of view, the pin-on-disk problem, only apparently simple, required very small time increments to correctly describe the circular trajectories of points, with high computational costs. Numerical strategies are currently under investigation to extend the study to the steady state phase of both tests.

The flow behavior of Fe-6.5wt.%Si alloys during hot compression was investigated at temperatures 650–950 °C and strain rates 0.01–10 s^-1. The results showed that the flow stress depended distinctly on the deformation temperatures and strain rates. The flow stress and work hardening rate increased with the decrease of temperature and the increase of strain rate. The activation energy under all the deformation conditions was calculated to be 410 kJ/mol. The constitutive equation with hyperbolic sine function and Zener–Hollomon parameter was developed. The peak stress, critical stress, and steady-state stress could be represented as σ=A+Bln(Z/A). Dynamic recrystallization occurred under the deformation conditions where the values of Z were lower than 10²⁰. Processing maps were established to optimize the processing parameters. The power dissipation efficiency decreased in the high temperature and low strain rate region, increased in the high temperature and high strain rate region, and remained unchanged in other regions with the increase of true strain. Furthermore, the unstable area expanded. The true strain of 0.7 was the optimum reduction according to the processing map. Based on the analysis of surface quality, microstructures, and ordered structures, the optimized processing parameters for the Fe-6.5wt.%Si alloys were the temperature and strain rate of higher than 900 °C and 0.01–10 s^-1, respectively, or 800–900 °C and lower than 0.4 s^-1, respectively.

Digital microfluidics (DMF) holds great potential for the alleviation of laboratory procedures in assisted reproductive technologies (ARTs). Electrowetting on dielectric (EWOD) provides dynamic culture conditions in vitro that may better mimic the natural embryo microenvironment. Thus far, EWOD microdevices have been proposed for in vitro gamete and embryo handling in mice and for analyzing the human embryo secretome. This article presents the development of the first microfluidic chip utilizing EWOD technology designed for the manipulation of bovine embryos in vitro. The prototype sustains the cell cycles of embryos manipulated individually on the chips during in vitro culture (IVC). Challenges related to the chip fabrication as well as to its application during bovine embryo IVC in accordance with the adapted on-chip protocol are thoroughly discussed, and future directions for DMF in ARTs are indicated.

Efficient use of the operating room (OR) is crucial for any hospital. One of the major inefficiencies in the OR is surgical cases not starting or finishing on time as scheduled. When a case is delayed, it affects all subsequent cases in that OR. This study uses discrete choice analysis to determine the significant factors, including team familiarity, that influence OR case on-time start and finish. A case is considered on-time if the documented procedure start and finish times are no more than 10 minutes after the scheduled start and finish times. The analysis uses surgical case data from a large tertiary referral hospital and academic center in Greenville, South Carolina. The case data includes all surgical cases (15,091) performed during regular workdays in 2013. Two binary logit models are developed: one for case on-time start and one for case on-time finish. Results indicate that higher team familiarity between surgeon and anesthesiologist, surgeon and circulating nurse, surgeon and scrub nurse, and surgeon and CRNA improve the likelihood of an OR case on-time start and on-time finish. This finding indicates that the OR scheduling staff in the study hospital make a concerted effort to schedule the surgical teams with members who have worked well together in the past.

Breast cancer is a common malignant tumour and studies have shown that early and accurate detection is crucial for patients. With the maturity of medical imaging and deep learning development, significant progress has been made in breast cancer classification, which greatly improves the accuracy and efficiency of classification. This review focuses on deep learning, migration learning, GAN, and lifelong learning to elaborate and summarise the important roles arising from breast cancer detection. This review also examines the dataset and labeling issues required for breast cancer classification. In conclusion, at the end of the article, we look at future directions for breast cancer classification research, including cross-migration learning, multimodal data fusion, model interpretability, and lifelong learning, and also explore how to provide personalized treatment plans for patients.

GaN nanowires grown on metal substrates attract an increasing interest for a wide range of applications. Herein, we report GaN nanowires grown by plasma-assisted molecular beam epitaxy on thin polycrystalline ZrN buffer layers, sputtered onto Si(111) substrates. The nanowire orientation is studied experimentally and described within a model as a function of the Ga beam angle, nanowire tilt angle and substrate rotation. We show that vertically aligned nanowires grow faster than inclined nanowires, which leads to an interesting effect of geometrical selection of the nanowire orientation in the directional molecular beam epitaxy technique. After a given growth time, this effect depends on the nanowire surface density. At low density, the nanowires continue to grow with random orientations as nucleated. At high density, the effect of preferential growth induced by unidirectional supply of material in MBE starts to dominate. Faster growing nanowires with smaller tilt angles shadow more inclined nanowires that grow slower. This helps to obtain more regular ensembles of vertically oriented GaN nanowires despite their random position induced by the metallic grains at nucleation. The obtained dense ensembles of vertically aligned GaN nanowires on ZrN/Si(111) surfaces are highly relevant for device applications. These results are not specific for GaN nanowires and should be relevant for any nanowires which are epitaxially linked to the randomly oriented surface grains in the directional molecular beam epitaxy.

Compressed Sensing (CS) MRI has shown great potential in enhancing time efficiency. Deep learning techniques, specifically Generative Adversarial Networks (GANs), have emerged as potent tools for speedy CS-MRI reconstruction. Yet, as the complexity of deep learning recon-struction models increases, this can lead to prolonged reconstruction time and challenges in achieving convergence. In this study we present a novel GAN-based model that delivers superior performance without escalating model complexity. Our generator module, built on the U-net architecture, incorporates dilated residual (DR) networks, thus expanding the network's receptive field without increasing parameters or computational load. At every step of the downsampling path, this revamped generator module includes a DR network, with the dilation rates adjusted according to the depth of the network layer. Moreover, we have introduced a channel attention mechanism (CAM) to distinguish between channels and reduce background noise, thereby fo-cusing on key information. This mechanism adeptly combines global maximum and average pooling approaches to refine channel attention. We conducted comprehensive experiments with the designed model using public domain MRI datasets of the human brain. Ablation studies af-firmed the efficacy of the modified modules within the network. Compared to other relevant models, our proposed model exhibits exceptional performance, achieving not only excellent sta-bility but also outperforming other networks in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The model presents a promising pathway for enhancing the efficiency and quality of CS-MRI reconstruction.

The fatigue crack growth rate (FCGR) of aluminium alloys under the combined influence of temperature and humidity remains a relatively unexplored area, receiving limited attention due to its intricate nature and challenges in predicting the combined impact of these factors. The challenge was to investigate and address the specific mechanisms and interactions between temperature and humidity, as in coastal environment conditions, on the FCGR of aluminium alloy. The present study conducts a comprehensive investigation on the combined influence of temperature and humidity on the FCGR of Al6082 alloy. The fatigue pre-cracked compact tension specimens were corroded for 7 days and then subjected to various temperature and humidity conditions in a thermal chamber for 3 days to simulate coastal environments. The obtained data were analysed to determine the influence of temperature and humidity on the FCGR of Al6082 alloy. An empirical model was also established to predict fatigue life cycle values under these environmental conditions precisely. The correlation between FCGR and fracture toughness models was also examined. The Al6082 alloy exhibits a 34% increase in the Paris constant C, indicating reduced FCGR resistance due to elevated temperature and humidity levels. At the same time, fatigue, corrosion, moisture-assisted crack propagation, and hydrogen embrittlement lead to a 27% decrease in threshold fracture toughness. The developed model exhibited accurate predictions for fatigue life cycles, and the correlation between fracture toughness and FCGR showed less than 10% error, indicating a strong relationship between these parameters.

High temperature titanium alloys are widely used in aerospace hot parts, however, the thermal barrier temperature of 600 oC limits its service temperature. In this paper, a two-step hot-dip plating method is proposed to prepare the composite coating containing Ce on the surface of titanium alloy, which can make the oxidation resistance temperature of titanium alloy reach 800 oC The microstructure, phase composition and element distribution of Ce-containing Ti-Al-Si hot-dip coating, Ce-containing Ti-Al-Si pre-oxidation coating and Ce-containing Ti-Al-Si high-temperature oxidation coating were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), respectively. The results show that the Ti-Al-Si hot-dip coating containing Ce is mainly composed of (Ti,Ce)(Al,Si)3 alloy phase layer, and the Ti-Al-Si pre-oxidation coating containing Ce is mainly composed of Ti-Al binary system phase layer and dense Al2O3 layer rich in CeO2. Ce in the high temperature oxidation coating of Ti-Al-Si containing Ce is mainly distributed in Ti3Al, TiAl, TiAl3+Ti5Si3 mixed phase layer and Al2O3. The addition of Ce can promote the formation of continuous Al2O3 layer, improve the uniformity of composite coating, prevent the spread of cracks, and improve the high temperature oxidation resistance of Ti-Al-Si coating.

Ultra-thin Fe–6.5wt.%Si ribbons with 35 μm in thickness were prepared by melt-spinning. The magnetic properties were investigated before and after annealing 1000 ºC. DC properties and low-frequency (400 Hz ~ 10 kHz) iron losses have significantly improved after heat treatment. A simplified formula based on Steinmetz law which can be used to predict the AC iron loss is presented. According to the results of some iron losses data, a simplified formula has been determined, and the extent of AC iron losses can be predicted. The results obtained from the formula predict AC iron loss to a good degree. The method developed in this work could be extended to other magnetic materials for predicting AC iron loss with greater ease.

The necessity for effective intrusion detection systems (IDS) in big data environments has grown critical due to the rising prevalence of big data systems and the rising amount of security threats. Applying conventional intrusion detection methods to the enormous and intricate data produced by big data ecosystems presents difficulties. Deep learning, has proven to be exceptionally adept at deciphering complex, large-scale data. This study proposes a Deep Learning-based Intrusion Detection System (IDS) created specifically for the Big Data environment. Traditional intrusion detection systems struggle to efficiently identify and prevent cyber threats due to the ever-increasing volume and complexity of data in current networks. We suggest an IDS that makes use of Deep Learning (CNN, LSTM, GAN, etc.), to address this problem. These cutting-edge neural network topologies give the system the ability to process and analyze massive amounts of data for precise intrusion detection. Data collection, data preprocessing, feature engineering, DL model training, intrusion detection, warning generation, and reaction are some of the crucial parts of the suggested IDS. The data collection module mines the Big Data environment for network traffic, system logs, and security event information. To make sure the data is suitable for analysis, it is preprocessed. To improve the detection abilities of the DL models, important features are extracted from the data using feature engineering approaches.

This research paper presents a deep learning approach to early detection of skin cancer using image augmentation techniques. The authors propose a two-stage image augmentation technique that involves the use of geometric augmentation and generative adversarial network (GAN) to classify skin lesions as either benign or malignant. This research utilized the public HAM10000 dataset to test the proposed model. Several pre-trained models of CNN were employed, namely Xception, Inceptionv3, Resnet152v2, EfficientnetB7, InceptionresnetV2, and VGG19. Our approach achieved accuracy, precision, recall, and F1-score of 96.90%, 97.07%, 96.87%, 96.97%, respectively, which is higher than the performance achieved by other state-of-the-art methods. The paper also discusses the use of SHapley Additive exPlanations (SHAP), an interpretable technique for skin cancer diagnosis, which can help clinicians understand the reasoning behind the diagnosis and improve trust in the system. Overall, the proposed method presents a promising approach to automated skin cancer detection that could improve patient outcomes and reduce healthcare costs.

Image fusion is the process of combining multiple input images from single or multiple imaging modalities into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. In this paper, we propose a novel method based on deep learning for fusing infrared images and visible images, named the LBP-based proportional input generative adversarial network (LPGAN). In the image fusion task, the preservation of structural similarity and image gradient information is contradictory, and it is difficult for both to achieve good performance at the same time. To solve this problem, we innovatively introduce Local Binary Patterns (LBP) into Generative Adversarial Networks (GANs), which effectively utilize the texture features of the source images, so that the network has stronger feature extraction ability and anti-interference ability. In the feature extraction stage, we introduce a pseudo-siamese network for the generator to extract the detailed features and the contrast features. At the same time, considering the characteristic distribution of different modal images, we propose a 1:4 scale input mode. Extensive experiments on the publicly available TNO dataset and CVC14 dataset show that the proposed method achieves the state-of-the-art performance. We also test the universality of LPGAN through the fusion of RGB and infrared images on the RoadScene dataset. In addition, LPGAN is applied to multi-spectral remote sensing image fusion. Both qualitative and quantitative experiments demonstrate that our LPGAN can not only achieve good structural similarity, but also retain rich detailed information.

For the generation of representative volume elements a statistical description of the relevant parameters is necessary. These parameters usually describe the geometric structure of a single grain. Commonly, parameters like area, aspect ratio and slope of the grain relative to the rolling direction are applied. However, usually simple distribution functions like log normal or gamma distribution are used. Yet, these do not take the interdependencies between the microstructural parameters into account. To fully describe any metallic microstructure though, these interdependencies between the singular parameters need to be accounted for. To accomplish this representation, a machine learning approach was applied in this study. By implementing a Wasserstein generative adversarial network, the distribution, as well as the interdependencies could accurately be described. A validation scheme was applied to verify the excellent match between microstructure input data and synthetically generated output data.

Sensors became integrated through the control condition arrangement, either for visual, mechanical, biological, or chemical applications. New stuff is designed for detection, as Diluted Magnetic Semiconductors (DMS), and are considered attractive candidates that consist of a traditional 111- V, II-VI, or group IV semiconductor. Manganese Mn-doped GaN (Mn.Gac.N) epitaxial velum has a unique magnetic, visual and chemical properties in order to control system intelligent for detector design. The subject area of the magnetic properties of MnxGal-xN is on a large scale available, there are only a few studies on the visual properties and electrochemical properties of MnxGal-xN epitaxial velums. Where MnGaN velums were used in spintronic and opto-electronic applications according to their magnetic characterization and constructed MnGaN electrode are drop fabric potential for potentiometric sensor applications since they have good performance as ion-selective electrodes. The electrical and magnetic properties that allow the control of electron spin as well as complaint period, makes the materials ideal for spintronic applications. Designing such spintronic and optoelectronic devices based on MnxGal-xN requires a broader agreement of physical, visual, electrical and chemical properties epitaxial velums that are still seldom in the literature. This bailiwick displays the potential use of MnGaN semiconductor as an all solid-state potentiometric sensor for measuring anions in solutions in the control engineering field.

This research focuses on deriving the equation of motion for fermions on a ring. The paper proposes an alternative equation for fermions on the ring, incorporating a self-rotation angle denoted as $\Delta$, and explores its relationship with the original equation.

We propose a novel moving median estimator specifically designed for online detection of threshold crossings in multi-channel signals, such as extracellular neural recordings. This estimator offers two key advantages: a reduced sensitivity to outliers and the elimination of memory requirements for storing arrival times. Furthermore, its design facilitates parallel implementation on FPGAs, making it ideal for real-time processing of multi-channel recordings.

In this paper we investigate analytic automorphisms of complex topological vector spaces and their applications to linear and nonlinear transitive operators. We constructed some examples of polynomial automorphisms which show that a natural analogue of the Jacobian Conjecture for infinite dimensional spaces is not true. Also, we prove that any separable Fréchet space supports a transitive analytic operator which is not a polynomial. We found some connections of analytic automorphisms and algebraic bases of symmetric polynomials and applications to hypercyclisity of composition operators.

Among the thermophysical properties, the surface / interfacial tension, viscosity and density / molar volume of liquid alloys are the key properties for the modelling of microstructural evolution during solidification. Therefore, only reliable input data can yield accurate predictions preventing the error propagation in numerical simulations of solidification related processes. Due to experimental difficulties related to reactivity of metallic melts at high temperatures, the measured data are often unreliable or even lacking. The application of containerless processing techniques either leads to a significant improvement of the accuracy or makes the measurement possible at all. On the other side, accurate model predicted property values could be used to compensate the missing data; otherwise, the experimental data are useful for the validation of theoretical models. The choice of models is particularly important for the surface, transport and structural properties of liquid alloys representing the two limiting cases of mixing, i.e. ordered and phase separating alloy systems. To this aim, the thermophysical properties of the Fe-Si and Cu-Pb systems were analysed and the connections with the peculiarities of their mixing behaviours are highlighted.

Intermetallic alloys like e.g. Iron-Aluminides, Titanium-Aluminides or Molybdenum- Silizides are prospective materials for high-temperature applications. For additive manufacturing (AM) intermetallic structural materials are particularly challenging due to their high melting points, oxygen susceptibility and low temperature brittleness. The feasibility of manufacturing intermetallic Mo-Si-B alloys with the laser additive manufacturing process of direct energy deposition (DED) is demonstrated and recent results in characterizing rapidly solidified material with respect to correlations between process, composition and microstructures are presented. The possibility to dope the material with Yttrium oxide (Y2O3) for dispersion is successfully demonstrated. Current challenges, e.g. homogenous distribution of alloying elements and applicability are addressed.

The microstructures and mechanical properties of the hot-rolled Fe-6.5wt.%Si sheet are analyzed. The microstructure of the hot-rolled sheet is layered along the thickness direction. The surface exhibits fine and equiaxed grains, whereas the center part shows coarse and elongated grains with a <101> fiber texture along the rolling direction. Serrated flow behavior is observed during tensile deformation of both the hot-rolled sheet and its center samples at 350 °C; thus, the serrated flow of the hot-rolled sheet is mainly attributed to the serration of the center part. The analyses of dislocation configurations, ordered structures, and crystal orientation show that the serrated flow behavior results from the interaction of solutes with mobile dislocations. Mobile dislocations are pinned by combining parallel forest dislocations with the pipe diffusion of solution atoms. This study provides a new perspective for the deformation mechanism of the Fe-6.5wt.%Si alloy.

This work investigated the isothermal holding time dependence of the densification, microstructure, weight loss and tensile properties of Fe-Mn-Si powder compacts. Elemental Fe, Mn and Si powder mixtures with a nominal composition of Fe-28Mn-3Si (in weight percent) were ball milled for 5h and subsequently pressed under a uniaxial pressure of 400 MPa. The compacted Fe-Mn-Si powder mixtures were sintered at 1200 ℃ for 0, 1, 2 and 3 h, respectively. In general, the density, weight loss and tensile properties increased with the increase of isothermal holding time. A significant increase in density, weight loss and tensile properties occurred in the compacts isothermally holding for 1 h, as compared to those with no isothermal holding. However, further extension of isothermal holding time (2 and 3 h) only played a limited role in promoting the density and tensile properties. The weight loss of the sintered compacts was mianly caused by the sublimation of Mn in Mn depletion region on the surface layer of the sintered Fe-Mn-Si compacts. The length of the Mn depletion region increased as isothermal holding time increased. A single α-Fe phase was detected on the surface of all the sintered compacts, and the locations beyond the Mn depletion region were comprised of a dual dominant γ-austenite and minor ε-martensite.

Quantum image representation is a widely researched area of quantum computing. Currently developed methods use angle parameter of the rotation gate (e.g., the FRQI method), sequences of qubits (ex. NEQR method) or phase shift (ex. LPIQE method) for storing color information of pixels. All of those methods are affected by decoherence and other classical and quantum noise, which is an inseparable part of quantum computing in a NISQ (Noisy Intermediate Scale Quantum) era. These all phenomenons influence the measurements, its probability distribution over the measurement basis and, as the result, makes the extracted images not even similar to those, which was stored in quantum computers. Since this process is, in its foundation, quantum as well, the computational reversal of this process is possible. There are a lot of methods for error correction, mitigation and reduction, but all of them use quantum computer time, or additional qubits to achieve desired result. We report a successful use of the Generative Adversarial Network tuned for image-to-image translation in conjunction with PDU method, for error reduction in images encoded using LIPQE (Local Phase Image Quantum Encoding) method.

Federated learning (FL) has emerged as a crucial technology in today’s data-centric technological environment, enabling decentralized machine learning and safeguarding user privacy. This study introduces “Federated Operations (FedOps) Mobile,” a novel FL framework optimized for the dynamic and heterogeneous ecosystem of mobile devices. FedOps Mobile enhances traditional FL approaches for mobile devices by integrating real-time operational control and advanced on-device training capabilities using TensorFlow Lite and CoreML, addressing critical challenges in scalability, efficiency, and system heterogeneity. Our approach utilizes a wide range of devices, facilitated by intelligent client-selection mechanisms. This mechanism evaluates the capabilities and readiness of multiple devices per client to ensure fair and efficient network participation. The framework also utilizes remote device control for seamless task management and sustained engagement, enabling continuous learning without compromising the user experience. We conducted extensive experiments to validate the framework’s performance, focusing on three core aspects: operational efficiency, model personalization, and resource optimization in multi-device environments. The results demonstrate that the proposed method is effective for efficient client selection, energy consumption, and model optimization.

In this paper, a prototype of an automatic lab on PCB for agarose preparation and electrophoresis is developed. The dimensions of the device are 38×34 mm2 and includes a conductivity sensor for detecting the TAE buffer (Tris-Acetate-EDTA buffer), a microheater for mixing, a NTC thermistor for controlling the temperature, a LDR sensor for measuring the transparency of the mixture, and two electrodes for performing the electrophoresis. The agarose preparation functions are governed by a microcontroller. The device requires a PMMA structure to define the wells of the agarose gel, and to release the electrodes from the agarose. The maximum voltage and current that the system requires are 40 V to perform the electrophoresis, and 1 A for activating the microheater. The chosen temperature for mixing is 80ºC, with a mixing time of 10 min. In addition, the curing time is about 30 min. This device is intended to be integrated as a part of a larger lab on PCB system for DNA amplification and detection. However, it can be used to migrate DNA amplified in conventional thermocyclers. Moreover, the device can be modified for preparing larger agarose gels and performing electrophoresis in an automatic manner.

Organ-on-Chip is a game-changing technology born from the convergence of tissue engineering and microfluidic technology. Organ-on-Chip devices (OoCs) are expected to offer effective solutions to persisting problems in drug development and personalized disease treatments. This opinion paper surveys the current landscape in research, development, application and market opportunities for OoCs to help establishing a global and multi-stakeholder OoC ecosystem. Based on a bibliometric study, a market analysis, expert interviews, and panel discussions held at the ORCHID Vision Workshop (Stuttgart, 23 May 2018), we outline presently unmet needs, key challenges, barriers and perspectives of the field, and finally propose recommendations towards the definition of a comprehensive roadmap that could render OoCs realistic models of human (patho)physiology in the near future.

This research paper contributes to the literature of deterrence theory in general, and in particular with respect to white-collar crime, offering valuable inside by using a unique data set of fraud and violation of trust incidents for Paraguay. Descriptive evidence show a clear and continuous misallocation of funds and human capital, and therefore providing less efficient services for the public. Regression analysis suggests that clearance rate exerts a highly significant effect in deterring fraud but results are not clear for violation of trust incidents. Despite the limitations of available data, results confirm deterrence theory in Paraguay. However, to more than two-thirds of victims, not even the attempt was made to seek justice. As a side-result, it seems that a soft on crime strategy, induced from the former German penal code, has led to an increasing share of pre-trial diversion and therefore enhancing white-collar crimes like fraud and violation of trust due to impunity.

Biometric based access control system acts as a weapon against the challenges for reliable authentication mechanism. Although there are many advantages of biometric system, still it is vulnerable to attacks, which decline its security. This leads to propose a new approach to address these open issues and challenges for biometric data security. Smart card have been already used in past with various degree of success to store biometric credentials. Match-on-card biometric framework locks the biometric data inside the microcontroller of the smart card, which leads to minimal risks if card is lost or stolen. It is fast and accurate, balancing security and convenience by never exchanging user data outside the system of smart card and performs fingerprint enrollment as well as matching within a tamperproof environment of smart card.

To weaken the harm of Al-Si coating and increase the strength of welded joint, variable thickness of Ni foil (Ni, an austenitic formation element) was added into the lap laser welding Al-Si coated 22MnB5 hot stamping steel/galvanized steel joints. The joints' weld appearance, microstructure, and mechanical properties were explored. The weld altered from X-shape to Y-shape with the increased thickness of Ni foil. During welding, Al-Si coating was melted and diluted into the welding pool, forming δ-ferrite (a rich-Al phase with low toughness and strength) in FZ and FB. This phase deteriorated the strength of the joints. After adding Ni, the amount and size of the δ-ferrite phase decreased. With a significant thickness of Ni foil, δ-ferrite would disappear. However, a new phase (FM, rich-Ni phase) probably formed except PM(a no or negligible Ni phase). The heat-affected zone (HAZ) on the side of 22MnB5 comprised a coarse martensite zone, refined martensite zone, martensite+ferrite zone, and tempered martensite zone from the FZ to the basic material. HAZ on the side of galvanized steel mainly contained ferrite and pearlite. After adding Ni foil, the strength of the joint was more than that without Ni. The maximum strength of the joint can be up to 679MPa because of the disappearance of δ-ferrite. Meanwhile, the toughness of the joint increased. The fracture mode was from three mixed fractures(cleavage, quasi-cleavage, and dimple) to one fracture(dimple).

Near-infrared (NIR) photodetectors (PDs) have attracted much attention in noninvasive medical diagnosis and treatment. Especially, the self-filtered NIR PDs are highly demandable for tremendous biomedical application due to their strong ability in wavelength discrimination. In this work, we designed and then fabricated a Si micro-holes array/Graphene (Si MHA/Gr) van der Waals (vdW) Schottky NIR photodiode by using PbS quantum dots (QDs) coating. The device exhibits a unique self-filtered NIR response with a responsivity of 0.7 A/W at -1 V and a response time of 61 μs, which are higher than that without PbS QDs coating and even most of previous Si/Gr Schottky photodiodes. The light trapping of the Si MHA and the PbS QDs coating can be attributed to the high responsivity of the vdW photodiode. Furthermore, the presented NIR photodiode can also be integrated in photoplethysmography (PPG) for real-time heart-rate (HR) monitoring. The extracted HR is in great accord with the value measured with the patient monitor by analyzing the Fourier transform of the stable and reliable fingertip PPG waveform, suggesting its potential for practical applications.

The poor oxidation resistance of refractory high-entropy alloys (RHEAs) is a major obstacle for their use in high-temperature engineering applications. Anti-oxidation coating technology is an effective method for improving the oxidation resistance. In this paper, the Si-20Cr-20Fe coating was prepared on MoNbTaTiW RHEA by a fused slurry method. The microstructural evolution and compositions of the silicide coating under high-temperature oxidation environment were studied. The results show that the silicide coating could effectively prevent the oxidation of the MoNbTaTiW RHEA. The initial silicide coating had a double-layer structure; a high silicon-content layer mainly composed of MSi2 as the outer layer and a low silicon-content layer mainly contained M5Si3 as the inner layer. Under high-temperature oxidation conditions, the silicon element diffused from the silicide coating to the RHEA substrate while the oxidation of the coating occurred. After oxidation, the coating was composed of an outer oxide layer and an inner silicide layer. The silicide layer moved toward the inside of the substrate, led to the increase of its thickness. Compared with the initial silicified layer, its structure did not change significantly. The structure and compositions of the oxide layer on the outer surface strongly depended on the oxidation temperature. This paper provides a strategy for protecting RHEAs from oxidation at high-temperature environments.

Classification of pre-processed fMRI dataset using the functional connectivity(FC) based features is considered a challenging task due to high dimensional FC features set and smaller dataset size. To tackle this specific FC high dimensional features set and a smaller dataset size , We have proposed here a GAN based dataset augmenter to firstly train the GAN on the NYU Connectivity Features dataset and used the trained GAN to generate synthetic features per category and after getting sufficient number of features per category , A multi-head attention mechanism was used as a head for the classification . We name our proposed approach as "ASD-GANNet" which is End-To-End and does not require hand-crafted features as the multi-head attention mechanism focuses on the features that are more relevant . Moreover , We compared our results with the 06 available state-of-the-art techniques from the literature and Our proposed approach results using "NYU" site as a training set for generating GAN based synthetic dataset are promising. We achieved an overall 10-fold cross validation based accuracy of 82% ,sensitivity 82% and specificity 81% outperforming the available state-of-the art approaches. Sitewise comparison of our proposed approach also outperformed the the available state-of-the-art as out of the 17 sites our proposed approach has better results in the 10 sites.

Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium Nitride-based devices, specifically AlGaN/GaN High Electron Mobility Transistors (HEMTs) in a novel packaging design provided by STMicroelectronics S.r.l. The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of a packaging.

We have investigated the interfacial dislocations in InxGa1–xN/GaN (0 ≤ x ≤ 0.20) heterostructures using diffraction contrast analysis in a transmission electron microscopy. The analysis indicate that the structural properties of the interface dislocations depend on the indium composition. For lower indium composition up to x = 0.09, we observed that the screw-type dislocations and dislocation half loops occurred at the interface even though the former do not contributes toward elastic relaxation of the misfit strain in the InGaN layer. With the increase of indium composition (0.13 ≤ x ≤ 0.17), in addition to the network of screw-type dislocations, edge-type misfit dislocations were found generated with their density gradually increasing. For higher indium composition (0.18 ≤ x ≤ 0.20), all the interfacial dislocations are transformed into a network of straight misfit dislocations along the <10-10> directions leading to partially relaxation of the InGaN epilayer. The presence of dislocation half loops may be explained by slip on the basal plane, the formation of misfit dislocations are attributed to punch-out mechanism.

Generative models for images, audio, text and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods for human gesture recognition. The object of this research is to develop a generative model for skeletal human movement, allowing to control the action type of generated motion while keeping the authenticity of the result and the natural style variability of gesture execution. We propose to use a conditional Deep Convolutional Generative Adversarial Network (DC-GAN) applied to pseudo-images representing skeletal pose sequences using Tree Structure Skeleton Image format. We evaluate our approach on the 3D-skeleton data provided in the large NTU RGB+D public dataset. Our generative model can output qualitatively correct skeletal human movements for any of its 60 action classes. We also quantitatively evaluate the performance of our model by computing Frechet Inception Distances, which shows strong correlation to human judgement. Up to our knowledge, our work is the first successful class-conditioned generative model for human skeletal motions based on pseudo-image representation of skeletal pose sequences.

In most countries, the incidence of nasopharyngeal carcinoma (NPC) is no more than 1 per 100,000 for both men and women; however, it is much higher for men and women in Taiwan. The use of traditional Chinese medicine (TCM) as complementary and alternative medicine for the treatment of NPC and its treatment-related side effects has been increasing. The National Health Insurance (NHI) covers 99.6% of Taiwan’s residents. In the present population-based cohort study, we aimed to investigate the pattern of utilization of Chinese herbal products (CHPs) for NPC from 2001 through 2011 in Taiwan. We identified a total of 30294 patients with newly diagnosed NPC from the Registry for Catastrophic Illnesses Patient Database (RCIPD). Descriptive statistics and multiple logistic regression analysis were employed to estimate the adjusted odds ratios (aORs) for CHP utilization. From 2001 through 2011, 17816 patients aged ≥20 years were newly diagnosed with NPC. Of these, 4749 patients used TCM outpatient services for NPC treatment. TCM users were more likely to be women, young, residents of Central Taiwan, and white-collar workers. The most commonly prescribed formula CHP was Gan-Lu-Yin, followed by Xin-Yi-Qing Fei-Tang and Shan-Shen-Mai-Men-Dong-Tang. The most commonly prescribed single CHP was Hedyotis diffusa, followed by Radix Scrophulariae and Radix Ophiopogonis. These findings provide information regarding personalized therapies for NPC and can promote further clinical experiments and pharmacological research on CHPs for NPC treatment in Taiwan. Further well-designed randomized controlled studies and basic mechanistic studies should assess the safety and effectiveness of CHPs for NPC treatment.

The purpose of this study is to explore the effect of Environment, Social, and Governance (ESG) scores on Return on Assets (ROA), Risk-Adjusted Return on Capital (RAROC), and Tobin's Q on firm performance. This study used 37 non-financial companies listed on the IDX between 2018 and 2022 in Indonesia companies. Linear and nonlinear panel data regression methods were used on the ESG score and its pillars, resulting in eight different models. The study found a U-shaped impact of ESG scores and social and environmental pillars on ROA. There is a positive linear relationship between ESG scores and the environmental and governance pillars with RAROC, while the social pillar shows an inverted U-shaped effect. However, ESG and its environmental and social pillars have a negative linear relationship with Tobin's Q. The findings suggest the need to manage ESG initiatives strategically, aligning them with financial objectives and awareness of how ESG factors relate to profitability.

This research aimed to discover how to create a customer experience that includes FEEL, SENSE, THINK, ACT, and RELATE to increase satisfaction with the Subscription Video on Demand (SVoD) application. A descriptive quantitative method was used, and the sample was 423 respondents in Indonesia who had used the application for at least 1 month. Furthermore, this research used probability sampling using a technique for random sampling. Based on the data available, experience accounted for 0.509, or 50.9%, of the application satisfaction. With a beta value of 0.295, the FEEL variable was the only one in this study to significantly and positively affect customer satisfaction; the other variables, SENSE, THINK, ACT, and RELATE, had no discernible effects. It is anticipated that the theoretical foundation provided by this research will be beneficial to the entertainment industry, particularly the SVoD application sector. This includes the product and service development division that focuses on customer inner feelings and emotions.

Worldwide, among older adults, infection is the leading mortality cause; chronic nutritional deficits confer significant mortality risk and increase healthcare costs. The association of the Global Leadership Initiative on Malnutrition (GLIM)-defined malnutrition with infection-related mortality, especially with renal dysfunction in older patients, remains unevaluated. In older patients hospitalized with infection, stratified by renal function, we investigated the association of malnutrition severity with mortality. This single-center, retrospective cohort study of 1220 participants (age ≥65 years) admitted to Aichi Medical University from 2019 to 2020 used a multivariate Cox proportional hazards model to determine the association of GLIM-defined nutritional status (no, moderate, or severe malnutrition) with all-cause mortality. Compared to no malnutrition, moderate and severe malnutrition conferred significantly higher mortality (adjusted hazard ratio [confidence interval ]: 1.00 [reference], 1.76 [1.28-2.42], and 2.44 [1.78-3.33], respectively), with the highest all-cause mortality in malnutrition with a low estimated glomerular filtration rate (eGFR &lt;30 mL/min/1.73m2; 7.35 [4.57-11.8]) compared to no malnutrition and normal eGFR (≥60 mL/min/1.73m2). GLIM-defined malnutrition confers higher all-cause mortality risk in older adults with infection, especially those with renal dysfunction. This information enables the identification of high-risk older patients with infection and targeted clinical management of those with malnutrition, renal dysfunction, and infection.

Oncological changes in the prostate are a common cause of death among elderly men. Malignant cells are difficult to identify at early stages, which are asymptomatic. The patient often seeks medical assistance when the disease has already progressed, and the treatment is less effective. Early diagnosis of prostate cancer (PC) is thus one of the priority tasks of modern urology and healthcare in general. The aim of this study is the detection of microRNAs (miRNAs), which are known to be associated with PC. The detection of the target miRNAs in human plasma samples has been performed with a nanoribbon biosensor system, which was based on "silicon-on-insulator" structures (SOI-NR biosensor). In order to provide biospecific detection of the target miRNAs, the surface of individual nanoribbons has been modified with DNA oligonucleotide probes (oDNA probes), whose nucleotide sequences were complementary to those of the target miRNAs. The high detection sensitivity has been demonstrated with the use of model oDNAs, which are complementary to nanoribbon-immobilized oDNA probes, in buffer solutions. The sensitivity threshold was 1.1 × 10^-17 M. The successful detection of target miRNAs, isolated from real plasma samples of PC patients, has also been demonstrated. We believe that the development of highly sensitive nanotechnology-based biosensors for PC markers is a step towards personalized medicine.

The one pot hydrogenolysis/hydrogenation reaction of maltose to 2 moles of sorbitol has been carried out over different supported Cu catalysts in water at 180°C and 40 bar of H2. Only the catalysts supported on silicas were found to be effective in this reaction giving up to 86% yield in the desired product while the bare supports and the catalysts supported on alumina or silica alumina gave messy reactions. The peculiar activity of the two Cu/Silica systems tested was ascribed to high metal dispersion and suitable polarity of the catalyst surface. The reduced catalyst, exposing metallic Cu particles on the surface, showed unusual stability in the presence of water as a solvent and could be reused several times without any treatment.

Fluorescence-linked immunosorbent assay (FLISA) is a commonly used, quantitative technique for detecting biochemical based on antigen–antibody binding reactions using a well-plate platform. With the developments in the manufacturing technology of microfluidic systems, FLISA can be implemented onto microfluidic disk platforms, which allows the detection of trace biochemical with high resolutions. Apart from requiring a lower proportion of reagent (1/10), this method also reduces the time required for the entire process to less than an hour. The incubation process involves antigen–antibody binding reactions as well as the binding of fluorogenic substrates to target proteins. The protocol for FLISA on a microfluidic platform necessitates the appropriate execution of liquid reagent movements during each step in order to ensure sufficient binding reactions. Herein, we propose a novel microfluidic disk comprising a 3D incubation chamber. Vascular endothelial growth factor as concentration with ng mL-1 is detected sequentially using a benchtop process employing this 3D microfluidic disk. The 3D microfluidic disk is implemented without requiring manual intervention or additional procedures for liquid control. During the incubation process, microbead movement is controlled through centrifugal force, generated due to disk rotation, and gravitational force via bead sedimentation on the sloped floor of the chamber.

This paper aims to describe the geometrical structure and explicit expressions of family of finitely parametrized probability densities over smooth manifold $M$. The geometry of family of probability densities on $M$ are inherited from probability densities on Euclidean spaces $\left\{U_\alpha \right\}$ via bundle morphisms, induced by an orientation-preserving diffeomorphisms $\rho_\alpha:U_\alpha \rightarrow M$. Current literature inherits densities on $M$ from tangent spaces via Riemannian exponential map $\exp: T_x M \rightarrow M$; densities on $M$ are defined locally on region where the exponential map is a diffeomorphism. We generalize this approach with an arbitrary orientation-preserving bundle morphism; we show that the dualistic geometry of family of densities on $U_\alpha$ can be inherited to family of densities on $M$. Furthermore, we provide explicit expressions for parametrized probability densities on $\rho_\alpha(U_\alpha) \subset M$. Finally, using the component densities on $\rho_\alpha(U_\alpha)$, we construct parametrized mixture densities on totally bounded subsets of $M$. We provide a description of inherited mixture product dualistic geometry of the family of mixture densities.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated in microchannel structures and characterized with various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was post-processed using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of -47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg grating-based waveguide sensor demonstrates high potential for applications based on lab-on-a-chip concept.

The gut plays a key role in drug absorption and metabolism of orally ingested drugs. Additionally, characterization of intestinal disease processes are increasingly gaining more attention as gut health is an important contributor to our overall health. The most recent innovation to study intestinal processes in vitro is the development of gut-on-a-chip (GOC) systems. Compared to conventional in vitro models they offer more translational value, and many different GOC models have been presented over the past years. Here, we reflect on the almost unlimited choices in designing and selecting a GOC for preclinical drug (or food) development research. Four components that largely influence the GOC design are highlighted, namely 1) the biological research questions, 2) chip fabrication and materials, 3) tissue engineering, and 4) the environmental and biochemical cues to add or measure in the GOC. Examples are presented of GOC studies in the two major areas of preclinical intestinal research: 1) intestinal absorption and metabolism to study the oral bioavailability of compounds, and 2) treatment-orientated research for intestinal diseases. The last section of this review presents an outlook on the limitations to overcome in order to accelerate preclinical GOC research.

The SI unit of length, the Metre, is presently defined by taking the fixed numerical value of the fundamental constant `c', the invariant speed of light in vacuum. This definition has the same physical basis as the previous definition, as the length of the path travelled by light in vacuum during a time interval of 1/299 792 458 of a second. With the atomic standard second defined in terms of the ground state hyperfine transition in Caesium-133, this definition is supposed to provide a universally reproducible standard of length. However, this relies on Einstein's singular postulate that the relative velocity of light in vacuum is an invariant constant that is independent of any inertial motion of the reference laboratory. I argue that the basis of the definition of the standard metre should be changed to the specific form, "the length of the path equal to the two-way propagation of light in vacuum during a time interval of 1/299 792 458 of a second", to be compatible and consistent with the fact that it is only the two-way relative velocity that is consistent with being an invariant. The null result in the Michelson-Morley two-way experiment, and in all such experiments to date, is consistent with a Galilean one-way propagation of light (relative velocity $c'=c\pm v$) as well as an invariant relative velocity of light. All practical methods and protocols related to the implementation of length standard involve also a two-way propagation, not conforming to the present definition. Besides, this redefinition is absolutely necessary because the relative velocity of light in one-way propagation is indeed Galilean, and not an invariant, as proved here in multiple ways including a direct experiment.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.