Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Study on Characteristics of AlGaN/GaN Metal–Insulator–Semiconductor High‐Electron‐Mobility Transistors

A metal–insulator–semiconductor high‐electron‐mobility transistor (MIS‐HEMT) with Al2O3/SiN x (SiN x next to semiconductor) double insulators is proposed to obtain lower gate leakage and lower current collapse simultaneously and is comparatively studied in this article. SiN x directly next to the (Al)GaN induces fewer interface traps and provides better passivation, and Al2O3 can greatly reduce gate leakage. The Schottky gate HEMT and MIS‐HEMTs with single SiN x and Al2O3 layer are also fabricated for comparison. The proposed structure shows the lowest gate leakage and the lowest current collapse as well as better output, transfer, breakdown performance. Besides, this proposed structure shows low requirements on fabrication techniques and induces fewer interface traps. Moreover, to further explore the reason behind those superior performances, the gate leakage mechanisms under reverse and forward bias conditions are studied and the interface traps are compared through capacitance–voltage (C–V) measurements in those four kinds of devices. The experimental results demonstrate that the MIS‐HEMT with Al2O3/SiN x double insulators is a superior candidate for nitrides‐based MIS‐HEMT devices.
Concerning Two Classes of Non-Diophantine Arithmetics

We present two classes of abstract prearithmetics, {AM}M≥1 and {BM}M>0. The first one is weakly projective with respect to the nonnegative real Diophantine arithmetic R+ = (R+,+,×,≤R+ ), and the second one is projective with respect to the extended real Diophantine arithmetic R = (R,+,×,≤R). In addition, we have that every AM and every BM is a complete totally ordered semiring. We show that the projection of any series of elements of R+ converges in AM, for any M ≥ 1, and that the projection of any non-indeterminate series of elements of R converges in BM, for all M > 0. We also prove that working in AM, for any M ≥ 1, and in BM, for all M > 0, allows to overcome a version of the paradox of the heap.
Differentiation Mechanism of the New Human Form and Its Collaborative Development Relations with Natural Person

: The essence of differentiating the new human form is the substitutability of information carrier and the variability of material information. The existing system is the result of collaborative development, and the balance and stability of the system in the future still need to be maintained through collaboration. Therefore, natural persons and the new human form were, are, and will be in collaborative development in the future, which basis is the intelligent ecosystem jointly created by various human forms. Only the establishment of social institutions suitable for the intelligent ecosystem is the institutional basis to ensure the symbiosis.
Potential Mechanisms of the Improvement of Glucose Homeostasis in Type 2 Diabetes by Pomegranate Juice

Pomegranate is a polyphenol-rich fruit. Studies have shown that extracts prepared from its juice or from different parts of the pomegranate plant have various biological activities including antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, cardioprotective, and antidiabetic. The therapeutic potential has been attributed to various phytochemicals, including ellagic acid, punicic acid, flavonoids, anthocyanidins, anthocyanins, flavonols, and flavones. This review focuses on the scientific evidence of pomegranate juice as hypoglycemic, emphasizing the chemical composition and the possible mechanisms of action associated with this effect. Studies were identified using the PubMed, Scopus, and ISI Web of Science databases to identify relevant articles focused on the hypoglycemic effect of pomegranate juice. The physiological responses to pomegranate juice are reported here, including a decrease of oxidative stress damage, an increase of insulin-dependent glucose uptake, maintenance of β-cell integrity, inhibition of nonenzymatic protein glycation, an increase of insulin sensitivity, modulation of peroxisome proliferator-activated receptor-gamma, inhibition of α-amylase, inhibition of α-glucosidase and dipeptidyl peptidase-4, and decreases in inflammation. Overall, we found a significant hypoglycemic effect of pomegranate in in vitro and in vivo studies and we summarize the potential mechanisms of action.
Hydrogen Production from Sawdust Pyrolysis Catalysed by TiO2 Impregnated Al2O3 Nanoparticles

In the present study, the hydrogen production of wood sawdust pyrolysis catalysed by TiO 2 impregnated Al 2 O 3 (TiO 2 /Al 2 O 3 ) was investigated under temperatures of 600, 700 and 800 ℃. The catalyst preparation was made by wet impregnation method for enhanced hydrogen-rich gas production from catalytic pyrolysis of sawdust. Characterization and morphology of TiO 2 doped Al 2 O 3 nanoparticles were performed using X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) and the gas product was analysed by gas chromatography. The presented TiO 2 doped Al 2 O 3 catalyst showed the highest H 2 yield in sawdust pyrolysis as 17.04 mol/kg, and gas productivity 0.72 Nm 3 /kg biomass at temperatures of 800 °C. Furthermore, the carbon conversion rate of the sawdust pyrolysis was detected as 53.6% with the TiO 2 doped Al 2 O 3 catalyst. It was observed that TiO 2 doped Al 2 O 3 nanoparticles supplementation approximately 50% increased the hydrogen production of sawdust pyrolysis, compared to non-catalytic experiment of sawdust pyrolysis.
The interplay between replication capacity of HIV-1 and surrogate markers of disease.

BACKGROUND HIV-1 replication capacity (RC) of transmitted/founder viruses may influence the further course of HIV-1 infection. METHODS Replication capacities (RCs) of 355 whole genome primary HIV-1 isolates derived from samples acquired during acute and recent primary HIV-1 infection (PHI) were determined using a novel high throughput infection assay in primary cells. The RCs were used to elucidate potential factors that could be associated with RC during PHI. RESULTS Increased RC was found to be associated with increased set point viral load (VL), and significant differences in RCs among 13 different HIV-1 subtypes were discerned. Notably, we observed an increase in RCs for primary HIV-1 isolates of HIV-1 subtype B over a 17-year period. Associations were not observed between RC and CD4 count at sample date of RC measurement, CD4 recovery after initiation of antiretroviral treatment (ART), CD4 decline in untreated individuals, and acute retroviral syndrome severity scores. DISCUSSION These findings highlight that RCs of primary HIV-1 isolates acquired during the acute and recent phase of infection are more associated with viral factors, i.e., set point VL, than with host factors. Furthermore, we observed a temporal increase in RC for HIV-1 subtype B viruses over a period of 17 years.
MSF-Net: A Multiscale Supervised Fusion Network for Building Change Detection in High-Resolution Remote Sensing Images

Building change detection is a primary task in the application of remote sensing images, especially in city land resource management and urbanization process assesment. Due to the rich textural features of remote sensing images and the multiscale characteristics of buildings, it is still a huge challenge to effectively filter out irrelevant change information (e.g., roads) and fuse multiscale building features. To date, deep learning-based methods have demonstrated powerful capabilities in this field. To fill these gaps, this study proposes a multiscale supervised fusion network (MSF-Net), which is an attention mechanism-based approach for building change detection using bi-temporal high-resolution satellite imagery. Especially, we built a dual-context fusion module to obtain abundant global context information of buildings and suppressing irrelevant features. We also used channel attention mechanism, selective kernel convolution and multiscale supervision module to fuse multiscale feature of buildings. The ablation experiments verified the availability of these modules. The MSF-Net model has been tested on the LEVIR-CD building change detection dataset. Compared with other state-of-the-art change detection methods, the study showed that our method obtained 0.8866 and 0.8130 in F1-score and Intersection over Union (IOU), respectively. The results indicate that the MSF-Net method has stronger multiscale building feature extraction capability and suppression ability of irrelevant features, which could produce clearer building boundaries and more accurate building change maps.
EXPERIMENTAL STRATEGY FOR IN VITRO EVALUATION OF CYTOTOXIC / ANTITUMOR PROPERTIES OF NEW METAL COMPLEXES WITH DIFFERENT LIGANDS

PURPOSE. The aim of this study was to evaluate cytotoxic / antitumor properties of newly synthesized metal [Zn(II), Cu(II), Co(II), Ni(II), Zn(II)/Ag(I), Zn(II)/Au(I)] complexes with various ligands (Schiff bases, non-steroidal anti-inflammatory drugs, bile acids) and to introduce an optimized strategy for such investigations in our research activity. MATERIALS AND METHODS. Human and animal tumor and non-tumor cells were used as model systems. Short-term (3 – 96h) and long-term (> 2 weeks) experiments were carried out using cytotoxicity assays, cytological / immunocytochemical, biochemical and molecular-biological methods to assess the influence of the compounds on cell viability and proliferation and their ability to induce apoptosis/necrosis and/or autophagy. RESULTS. The examined metal complexes express cytotoxic activity that is time- and concentration-dependent and are more active than the corresponding ligands tested alone. Zn(II)/Au(I) and Zn(II)/Ag(I) complexes with Salen are found to be the most promising cytotoxic agents being effective also in multidrug resistant cancer cells. Their cytotoxic activity is higher than those of cisplatin, oxaliplatin and epirubicin. CONCLUSIONS. A complex approach, based on a wide range of cell cultures and methods with different molecular / cellular targets and mechanisms of action was optimized and successfully applied for the assessment of cytotoxicity of new metal complexes.
Potential Investigation of Membrane Energy Recovery Ventilators for the Management of Building Air-Conditioning Loads

The present study provides insights into the energy-saving potential of a membrane energy recovery ventilator (ERV) for the management of building air-conditioning loads. This study explores direct (DEC), Maisotsenko cycle (MEC) evaporative cooling, and vapor compression (VAC) systems with ERV. Therefore, this study aims to explore possible air-conditioning options in terms of temperature, relative humidity, human thermal comfort, wet bulb effectiveness, energy saving potential, and CO2 emissions. Eight different combinations of the above-mentioned systems are proposed in this study i.e., DEC, MEC, VAC, MEC-VAC, and their possible combinations with and without ERVs. A building was modeled in DesignBuilder and simulated in EnergyPlus. The MEC-VAC system with ERV achieved the highest temperature gradient, wet bulb effectiveness, energy-saving potential, optimum relative humidity, and relatively lower CO2 emissions i.e., 19.7 °C, 2.2, 49%, 48%, and 499.2 kgCO2/kWh, respectively. Thus, this study concludes the hybrid MEC-VAC system with ERV the optimum system for the management of building air-conditioning loads.
Zingiber officinale attenuates 6-hydroxydopamine induced oxidative stress and apoptosis through AKT, Nrf2, MAPK, NF-κB signaling pathway in PC12 cells

To explore the protective impact of the ginger root ethanol extract (GRE) against the oxidative stress induced by 6-hydroxydopamine (6-OHDA) and apoptotic and its mechanism. Parkinson’s disease (PD) model was established using 6-OHDA in the cells of rat adrenal pheochromocytoma (PC12). The GRE pretreatment increased PC12 cell viability of injury induced by 6-OHDA. The GRE effectively suppressed 6-OHDA-induced death, apoptosis through decreased Bax and cleaved-caspase 3 expression, and up-regulated expression of B-cell lymphoma 2 (Bcl-2). GRE also inhibited 6-OHDA-inducel oxidative stress, decreased reactive oxygen species (ROS) and up-regulates the heme oxygenase (HO-1), antioxidant enzymes, catalase and, glutathione (GSH), superoxide dismutase (SOD), 8-oxoguanine glycosylase1 (OGG1) and NAD(P)H quinone oxidoreductase1 (NQO1). Besides, GRE up-regulating Protein kinase B (Akt), nuclear erythroid 2-related factor 2 (Nrf2), down-regulating nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) translocation, together with the mitogen-activated protein kinase (MAPK) phosphorylation. In conclusions, the GRE prevented apoptosis and oxidative stress in 6-OHDA-induced PC12 cells. The ginger ethanol extract could be treatment and prevention of PD.
Research on Underwater Acoustic Environment Simulation and Visualization

Aiming at the strong influence of underwater acoustic environment for the power of sonar detecting and the ocean environmental feature of ocean battlefield,the simulating models of sound propagation in shallow water and deep sea were established,which provided rapid and accurate prediction of underwater acoustic environment for navy operation.Based on the three dimensional sound field textures the pre-integrated volume rendering method was proposed.The method gave an intuitionistic description and analysis for the spatial structure of sound field and offered an efficient way for awareness,simulating training and operational decision of underwater acoustic environment.
A Machine Vision Anomaly Detection System to Industry 4.0 Based on Variational Fuzzy Autoencoder

From a technological point of view, Industry 4.0 evolves and operates in a smart environment in which the real and virtual worlds come together through smart cyber-physical systems. These devices that control each other autonomously activate innovative functions that enhance the production process. However, the industrial environment in which the most modern digital automation and information technologies are integrated is an ideal target for large-scale targeted cyberattacks. Implementing an integrated and effective security strategy in the Industrial 4.0 ecosystem presupposes a vertical inspection process at regular intervals to address any new threats and vulnerabilities throughout the production line. This view should be accompanied by the deep conviction of all stakeholders that all systems of modern industrial infrastructure are a potential target of cyberattacks and that the slightest rearrangement of mechatronic systems can lead to generalized losses. Accordingly, given that there is no panacea in designing a security strategy that fully ensures the infrastructure in question, advanced high-level solutions should be adopted, effectively implementing security perimeters without direct dependence on human resources. One of the most important methods of active cybersecurity in Industry 4.0 is the detection of anomalies, i.e., the identification of objects, observations, events, or behaviors that do not conform to the expected pattern of a process. The theme of this work is the identification of defects in the production line resulting from cyberattacks with advanced machine vision methods. An original variational fuzzy autoencoder (VFA) methodology is proposed. Using fuzzy entropy and Euclidean fuzzy similarity measurement maximizes the possibility of using nonlinear transformation through deterministic functions, thus creating an entirely realistic vision system. The final finding is that the proposed system can evaluate and categorize anomalies in a highly complex environment with significant accuracy.
Identifying information friction in teacher professional development: insights from teacher-reported need and satisfaction

ABSTRACT Professional Development (PD) is regarded a critical channel through which teacher instructional effectiveness improves. However, research shows that teacher discontent with PD is widespread. Bridging literature in organisational decision and labour economics, this study theorises that variation in how schools collect, process and respond to information on teacher needs can influence the degree of information friction in PD provision. Applying a two-step empirical analysis to the Teaching and Learning International Survey (TALIS) 2013 and 2018 United States sample (n = 4,336), findings reveal that teachers demonstrate high levels of concentrated PD need, yet schools do not meet these reported needs. Regression analysis results show that those schools demonstrating higher degrees of plurality in leadership and school autonomy are more effective in addressing teacher needs, while the effect of principal-staff interaction is more complex. Findings contribute new evidence on information friction in teacher PD provisionand identify effective management means in addressing information problems in school settings.
Density Regression with Conditional Support Points

Abstract Density regression characterizes the conditional density of the response variable given the covariates, and provides much more information than the commonly used conditional mean or quantile regression. However, it is often computationally prohibitive in applications with massive datasets, especially when there are multiple covariates. In this article, we develop a new data reduction approach for the density regression problem using conditional support points. After obtaining the representative data, we exploit the penalized likelihood method as the downstream estimation strategy. Based on the connections among the continuous ranked probability score, the energy distance, the L 2 discrepancy and the symmetrized Kullback–Leibler distance, we investigate the distributional convergence of the representative points and establish the rate of convergence of the density regression estimator. The usefulness of the methodology is illustrated by modeling the conditional distribution of power output given multivariate environmental factors using a large scale wind turbine dataset.
Survey on Device to Device (D2D) Communication for 5GB/6G Networks: Concept, Applications, Challenges, and Future Directions

Device-to-device (D2D) communication is one of the most promising technologies in wireless cellular networks that can be employed to improve spectral and energy efficiency, increase data rates, and reduce links latency. This paper investigates fifth generation and beyond (5GB) networks, the basics of D2D communication, applications, and classification. Herein, D2D in in-band (IBD) and out-band (OBD) modes are discussed. This paper also presents the integration of D2D communication with other prominent technologies and demonstrates the importance of integration with possible solutions in improving network performance. We further investigate the challenges of D2D communication, opportunities, and future research directions of D2D in 5GB networks. In addition, D2D communication in 6G network challenges and open research areas are introduced.
Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes.
Fault Current Limiters Based Dynamic Segmentation Technique for Multi-infeed HVDC Systems

In order to improve the performance of the multi-infeed HVDC systems,a grid dynamic segmentation technique based on the fault current limiters was proposed in this paper.The basic idea of the technique was to install the fault current limiters on the appropriate AC lines according to the network structure and to segment the power grid into a number of sectors connected by these fault current limiters.The equivalent impendence of the fault current limiters is zero under normal conditions and does not affect the power flow and the voltage of the system.When short-circuit faults occur inside the AC system,the current-limiting impendence is inserted to limit the short-circuit current and obstruct the propagation of the faults among the sectors.As a result,the commutation failure duration of the DC systems is shorten,the recovery of the DC systems is sped,the power imbalance and the transferred system flow caused by the concurrent commutation failures of the multi-infeed HVDC systems are relieved,and the transient stability of the system is improved significantly.The simulation results of two representative multi-infeed HVDC systems verified the effectiveness of the proposed technique.
Wavefront Decomposition and Propagation Through Complex Models with Analytical Ray Theory and Signal Processing

We present a novel method which can perform the fast computation of the times of arrival of seismic waves which propagate between a source and an array of receivers in a stratified medium. This method combines signal processing concepts for the approximation of interfaces and wavefronts, and ray theory for the propagation of wavefronts. This new approach leads to the redefinition and simplification of the model through which waves propagate. The modifications are governed by the spectral characteristics of the source signal. All rays are computed without any omission at a much lower cost in computing time than classical methods
EFFECTS OF USER COMMUNITY SENSING CAPABILITY IN DIGITAL PRODUCT INNOVATION: EVIDENCE FROM THE VIDEO GAME INDUSTRY

Digital technology continues to extend the co-creative role of users and user communities as sources of innovation-conducive knowledge. While the potential of user communities in this context is well established, little is known about the capabilities needed to successfully manage the interface with virtual user communities. The paper investigates User Community Sensing (UCS) capability as a measure of firms’ ability to anticipate changes and opportunities for innovation by interfacing with relevant user communities. Based on existing research and data from 173 product innovation projects, the study employs structural equation modelling to test the hypothesised effects of this capability on product innovation performance and product innovation speed. The results indicate that UCS capability affects performance positively and indirectly by increasing knowledge about users but has no significant effect on speed. As well as contributing to the literature on innovation management, the study has a number of implications for practitioners.