Search Results (267)

Digital transformation in government services represents a strategic shift that leverages digital technologies to enhance efficiency, accessibility, convenience, and user-centricity. In the wake of the COVID-19 pandemic, many governments accelerated the digitisation of services to support remote access and social distancing. Governments typically progress from digitisation (converting physical processes into digital formats) to digitalisation (automating service delivery and improving process efficiency), and ultimately to full digital transformation, where services are completed instantly and entirely online. However, varying levels of maturity across countries influence service outcomes differently, and indicators related to service quality, convenience, and security remain underexamined, particularly in developing contexts. This study addresses these gaps by examining Kuwait’s progress along the digitalisation–digital transformation continuum. It investigates current trends and user preferences in the use of digital government services based on empirical quantitative data collected from users in Kuwait. Specifically, the research objectives are fourfold: (i) to identify crucial outcome metrics for the success of digital government services, (ii) to assess user evaluations of these services according to these metrics, (iii) to examine significant differences between digital transformation and digitalisation services, and (iv) to develop and empirically test a model for evaluating digital transformation success. Drawing on established Information Systems’ (ISs’) success perspectives, a customised conceptual model incorporating six outcome metrics in three domains—service-related (user satisfaction, service quality), convenience-related (accessibility, ease of use), and security-related (perceived security, perceived trust)—was developed. A survey of 378 users of digital government services in Kuwait was conducted to compare perceptions across service types using independent-samples t-tests and linear regression analyses. The study found that users primarily accessed government services through smartphones and dedicated applications, highlighting the importance of mobile optimisation, and showed a clear preference for real-time, fully automated services over those requiring extended approval processes. The results indicate that digital transformation services significantly outperform digitalisation services across five outcome metrics—satisfaction, service quality, accessibility, ease of use, and perceived security—while trust remains consistent across both. These findings underscore the importance of advancing comprehensive digital transformation to enhance public service delivery. Practical recommendations are provided to support Kuwait’s digital government strategy. Given the purposive sampling and cross-sectional, comparative design, the findings should be interpreted with caution, and future studies are encouraged to apply probability-based sampling and more advanced multivariate techniques (e.g., structural equation modelling) to validate and extend the proposed model. Full article

This study develops an automatic dispatch system for quadrotor UAVs that integrates air-writing gesture recognition with a graphical user interface (GUI). The DJI RoboMaster quadrotor UAV (DJI, Shenzhen, China) was employed as the experimental platform, combined with an ESP32 microcontroller (Espressif Systems, Shanghai, China) and the RoboMaster SDK (version 3.0). On the Python (version 3.12.7) platform, a GUI was implemented using Tkinter (version 8.6), allowing users to input addresses or landmarks, which were then automatically converted into geographic coordinates and imported into Google Maps for route planning. The generated flight commands were transmitted to the UAV via a UDP socket, enabling remote autonomous flight. For gesture recognition, a Raspberry Pi integrated with the MediaPipe Hands module was used to capture 16 types of air-written flight commands in real time through a camera. The training samples were categorized into one-dimensional coordinates and two-dimensional images. In the one-dimensional case, X/Y axis coordinates were concatenated after data augmentation, interpolation, and normalization. In the two-dimensional case, three types of images were generated, namely font trajectory plots (T-plots), coordinate-axis plots (XY-plots), and composite plots combining the two (XYT-plots). To evaluate classification performance, several machine learning and deep learning architectures were employed, including a multi-layer perceptron (MLP), support vector machine (SVM), one-dimensional convolutional neural network (1D-CNN), and two-dimensional convolutional neural network (2D-CNN). The results demonstrated effective recognition accuracy across different models and sample formats, verifying the feasibility of the proposed air-writing trajectory framework for non-contact gesture-based UAV control. Furthermore, by combining gesture recognition with a GUI-based map planning interface, the system enhances the intuitiveness and convenience of UAV operation. Future extensions, such as incorporating aerial image object recognition, could extend the framework’s applications to scenarios including forest disaster management, vehicle license plate recognition, and air pollution monitoring. Full article

Driven by 5G/6G and the Internet of Things (IoT), wireless sensor networks (WSNs) are confronted with core challenges such as limited energy constraints, unbalanced resource allocation, and security vulnerabilities. To address these, WSNs are integrated with cognitive radio networks (CRNs) to alleviate spectrum scarcity, and reconfigurable intelligent surfaces (RIS) are adopted to enhance performance, but traditional passive RIS suffers from “double fading” (signal path loss from transmitter to RIS and RIS to receiver), which undermines WSNs’ energy efficiency and the physical layer security (PLS) (e.g., secrecy rate, SR) of primary users (PUs) in CRNs. This study leverages symmetry to develop an active RIS framework for WSN-integrated CRNs, constructing a tripartite collaborative model where symmetric beamforming and resource allocation improve WSN connectivity, reduce energy consumption, and strengthen PLS. Specifically, three symmetry types—resource allocation symmetry, beamforming structure symmetry, and RIS reflection matrix symmetry—are formalized mathematically. These symmetries reduce the degrees of freedom in optimization (e.g., cutting precoding complexity by ~50%) and enhance the directionality of green interference, while ensuring balanced resource use for WSN nodes. The core objective is to minimize total transmit power while satisfying constraints of PU SR, secondary user (SU) quality-of-service (QoS), and PU interference temperature, achieved by converting non-convex SR constraints into solvable second-order cone (SOC) forms and using an alternating optimization algorithm to iteratively refine CBS/PBS precoding matrices and active RIS reflection matrices, with active RIS generating directional “green interference” to suppress eavesdroppers without artificial noise, avoiding redundant energy use. Simulations validate its adaptability to WSN scenarios: 50% lower transmit power than RIS-free schemes (with four CBS antennas), 37.5–40% power savings as active RIS elements increase to 60, and a 40% lower power growth slope in multi-user WSN scenarios, providing a symmetry-aided, low-power solution for secure and efficient WSN-integrated CRNs to advance intelligent WSNs. Full article

This study examines cosmic acceleration in the framework of $f(Q,T)$ gravity and compares it to the standard $\Lambda$CDM model. It considers a generalized nonlinear form of the nonmetricity, expressed as $f(Q,T)=-Q+{\alpha }_0{Q}^2/H_0^2+{\beta }_{0}T+{\eta }_0$, where ${\alpha }_0,{\beta }_0,$ and ${\eta }_0$ are constants, and $H_0$ is the current value of the Hubble constant. In the solution process, we did not rely on any additional conditions to solve the field equations; instead, the field equations were reduced to a time-dependent closed system of nonlinear first-order coupled differential equations for H and $\rho$. Subsequently, these differential equations were converted to the redshift space for numerical integration alongside the Runge–Kutta method. Furthermore, the study demonstrates that the deceleration parameter q changes sign from being positive in an early period of time at high redshift values to a negative value, passing through a transitional redshift $z_t\approx [0.766,0.769,0.771]$ and $z_t\approx [0.521,0.770,1.010]$, reaching their current values at $q_0=[-0.61,-0.60,-0.59]$ and $[-0.455,-0.595,-0.694]$ for different values of ${\beta }_0$ and ${\alpha }_0$, respectively. Similarly, the effective equation of state $w_{eff}$ shifted from the matter-dominated phase $w_{eff}=0$ at high redshift to a quintessence-like behavior at low redshift. Moreover, a super-accelerated or phantom-like regime with $q_0\simeq -1.59$ and $w_{\mathrm{eff},0}\simeq -1.40$ was obtained when ${\alpha }_0=0.55$ and ${\beta }_0=0.60$ were employed. The model analysis reveals that the universe is presently experiencing an accelerating expansion phase, propelled by a quintessence-type and phantom-like dark energy component, as corroborated by the Om(z) diagnostic test. The results obtained were strongly consistent with the concordance $\Lambda$CDM model. Full article

As a continuation of Part I on the structure and regulation of factor VII-activating protease (FSAP), this narrative review synthesizes mechanistic, translational, and limited clinical evidence to delineate FSAP’s roles at the interface of coagulation and fibrinolysis. Current evidence indicates that FSAP enhances thrombin generation primarily via proteolytic inactivation of tissue factor pathway inhibitor (TFPI), whereas direct activation of factor VII (FVII) by FSAP appears weak or context-restricted. Beyond plasma proteins, FSAP can upregulate tissue factor (TF) in human macrophages, while platelet-related effects remain insufficiently substantiated. On the fibrinolytic axis, FSAP indirectly accelerates clot lysis by converting single-chain urokinase (scuPA) to its active two-chain form (tcuPA) and, less efficiently, by processing tissue-type plasminogen activator (tPA); in addition, selective cleavage of fibrinogen Aα and Bβ chains remodels clot architecture, yielding thinner fibers with higher density and increased susceptibility to proteolysis. Collectively, the data position FSAP as a context-sensitive modulator of thrombin generation and fibrin turnover. Key gaps include isoform specificity, in vivo cellular targets, and the quantitative contribution of the FSAP-TFPI and FSAP–fibrinogen–urokinase/tPA axes in human pathophysiology, which warrant focused mechanistic and clinical studies. Full article

Reprogramming of macrophages into the inflammatory state (also known as M1) is currently considered as an effective way of eliminating cancer cells, but systemic deployment of this strategy is likely to induce dangerous autoimmune reactions. Consequently, converting immunosuppressive M2-type macrophages into M1 systemically is not a safe and effective therapeutic approach against cancer. Through cleavable covalent linking of curcumin to the chemotherapeutic agent Paclitaxel (Taxol), we have created a novel prodrug (STO-1) that, upon intravenous delivery, selectively reprograms tumor-associated microglia and macrophages (TAMs) and eliminates glioblastoma (GBM) without triggering autoimmunity. Demonstrating its therapeutic efficacy, prolonged treatment of six orthotopic GBM-bearing mice with STO-1 resulted in 67% long-term survival, with three surviving mice exhibiting complete tumor clearance and one displaying minimal residual disease, as confirmed by high-resolution ex vivo T2-weighted MRI 85 days after tumor inoculation. In contrast, the vehicle-treated mice displayed extensive intracranial tumors with edema and hemorrhage. Mechanistically, scRNA-seq analysis indicated induction of multiple M1-associated transcripts (ccrl2, cxcl9, ccr2, ccl5) consistent with robust TAMs reprogramming. In striking contrast to the M2⟶M1 reprogramming of TAMs, M1-type macrophages were suppressed in the spleens of STO-1-treated cancer-free mice. Therefore, STO-1 induces selective anti-tumor immunity and GBM elimination without triggering systemic autoimmune reactions. Full article

For power electronic transformer (PET) based Modular Multilevel DC-Link Based T-type Converters (MMDTC) with Double Active Bridges (DABs) (namely DABs-based MMDTC-PET), the sub-module capacitor voltages exhibit relatively large ripples. To reduce the voltage ripple of sub-module capacitors, this paper proposes a novel MMDTC-PET structure that utilizes the Three-Port Active Bridges (TABs) to replace the DABs as the isolation stage (TABs-based MMDTC-PET). When the two full bridges of the TAB on the primary side adopt identical phase-shift modulation, the two sub-module capacitors within the upper and lower arms form a parallel connection. This configuration endows the sub-module capacitors with switched-capacitor characteristics, suppressing voltage ripple in the sub-module capacitors and enabling power ripple flow to the secondary side. Meanwhile, by leveraging the characteristic that the AC power components of the upper and lower arm sub-modules have equal amplitudes but opposite phases, these AC power components are mutually canceled on the secondary side of the TAB. Simulation and experimental results verify the effectiveness of the proposed scheme. Full article

With the development of embedded electronic devices, energy consumption has become a significant design issue in modern systems-on-a-chip. Conventional SRAMs cannot maintain data after powering turned off, limiting their use in applications such as battery-powered smartphone devices that require non-volatility and no leakage current. RRAM devices are recently used extensively in applications such as self-charging wireless sensor networks and storage elements, owing to their intrinsic non-volatility and multi-bit capabilities, making them a potential candidate for mitigating the von Neumann bottleneck. We propose a new RRAM-based hybrid memristor model incorporated with a permanent magnet. The proposed design (1T2R) was simulated in Cadence Virtuoso with a 1.5 V power supply, and the finite-element approach was adopted to simulate magnetization. This model can retain the data after the power is off and provides fast power on/off transitions. It is possible to charge a smartphone battery without an external power source by utilizing a portable charger that uses magnetic induction to convert mechanical energy into electrical energy. In an embedded smartphone self-charging device this addresses eco-friendly concerns and lowers environmental effects. It would lead to the development of magnetic field-assisted embedded portable electronic devices and open the door to new types of energy harvesting for RRAM devices. Our proposed design and simulation results reveal that, under usual conditions, the magnet-based device provide a high voltage to charge a smartphone battery. Full article

This paper addresses a critical challenge in Modular Multilevel DC-link based T-type Converter (MMDTC) battery energy storage systems: the inherent power symmetry between upper and lower arms that prevents natural state-of-charge (SOC) balancing. A novel inter-arm SOC balancing control strategy is proposed that precisely modulates arm valley voltage characteristics—both amplitude and duration—to create controlled power differentials between arms. The theoretical analysis establishes a quantitative relationship between arm valley voltage width and inter-arm power difference, demonstrating that SOC balancing time is inversely proportional to arm valley voltage width. A key advantage of the proposed approach is its adaptive regulation capability: during steady-state operation, closed-loop feedback maintains arm valley voltage width within a narrow range through real-time SOC differential assessment, ensuring dynamic SOC equilibrium while minimizing impact on output power quality. The strategy works effectively in both charging and discharging modes, with comprehensive control logic for various operational scenarios. Finally, simulation and experimental results confirmed the effectiveness of the proposed control strategy. Full article

Background/Objectives: Selective inhibition of bacterial virulence factors is a promising strategy to convert pathogenic bacteria into non-pathogenic commensals, circumventing the challenge of antibiotic resistance. This approach enables the host immune system to eliminate virulence-attenuated pathogens. Methods: In this study, we evaluated the effects of Lindera obtusiloba Blume extract and cinnamtannin B1, the active component of the ethyl acetate fraction, on the type III secretion system (T3SS) of Yersinia enterocolitica. Results: The ethyl acetate fraction, at 100 mg/L, effectively suppressed all three T3SS components—the flagellar, Ysa, and Ysc T3SSs. Cinnamtannin B1, isolated from the ethyl acetate fraction through separation and identified through nuclear magnetic resonance spectrometer analysis, significantly inhibited flagellar and Ysa T3SS secretion, while selectively inhibiting expression of key effector proteins YopH and YopO in the Ysc T3SS. Additionally, cinnamtannin B1 reduced Y. enterocolitica-induced RAW 264.7 macrophage mortality and prevented poly (ADP-ribose) polymerase degradation, a marker of apoptosis. Conclusions: These findings suggest cinnamtannin B1 from L. obtusiloba as a selective T3SS-targeting compound with mechanistic potential for anti-virulence intervention. Further in vivo validation will be necessary to evaluate its therapeutic applicability. Full article

The increasing penetration of electrified vehicles is accelerating the evolution of on-board and off-board charging systems, which must deliver higher efficiency, power density, safety, and bidirectionality under increasingly demanding constraints. This article presents a system-level review of state-of-the-art charging architectures, with a focus on galvanically isolated power conversion stages, wide-bandgap-based switching devices, battery pack design, and real-world implementation trends. The analysis spans the full energy path—from grid interface to battery terminals—highlighting key aspects such as AC/DC front-end topologies (Boost, Totem-Pole, Vienna, T-Type), high-frequency isolated DC/DC converters (LLC, PSFB, DAB), transformer modeling and optimization, and the functional integration of the Battery Management System (BMS). Attention is also given to electrochemical cell characteristics, pack architecture, and their impact on OBC design constraints, including voltage range, ripple sensitivity, and control bandwidth. Commercial solutions are examined across Tier 1–3 suppliers, illustrating how technical enablers such as SiC/GaN semiconductors, planar magnetics, and high-resolution BMS coordination are shaping production-grade OBCs. A system perspective is maintained throughout, emphasizing co-design approaches across hardware, firmware, and vehicle-level integration. The review concludes with a discussion of emerging trends in multi-functional power stages, V2G-enabled interfaces, predictive control, and platform-level convergence, positioning the on-board charger as a key node in the energy and information architecture of future electric vehicles. Full article

Partial discharge (PD) is a critical indicator of insulation degradation in high-voltage DC systems, necessitating accurate diagnosis to ensure long-term reliability. Conventional AC-based diagnostic methods, such as phase-resolved partial discharge analysis (PRPDA), are ineffective under DC conditions, emphasizing the need for waveform-based analysis. This study presents a novel clustering framework for DC PD pulses, leveraging multi-level wavelet decomposition and statistical feature extraction. Each signal is decomposed into multiple frequency bands, and 70 distinctive waveform features are extracted from each pulse. To mitigate feature redundancy and enhance clustering performance, principal component analysis (PCA) is employed for dimensionality reduction. Experimental data were obtained from multiple defect types and measurement distances using a 22.9 kV cross-linked polyethylene (XLPE) cable system. The proposed method significantly outperformed conventional time-frequency (T-F) mapping techniques, particularly in scenarios involving signal attenuation and mixed noise. Propagation-induced distortion was effectively addressed through multi-resolution analysis. In addition, field noise sources such as HVDC converter switching transients and fluorescent lamp emissions were included to assess robustness. The results confirmed the framework’s capability to distinguish between multiple PD types and noise sources, even in challenging environments. Furthermore, optimal mother wavelet selection and correlation-based feature analysis contributed to improved clustering resolution. This framework supports robust PD classification in practical HVDC diagnostics. The framework can contribute to the development of real-time autonomous monitoring systems for HVDC infrastructure. Future research will explore incorporating temporal deep learning architectures for automated PD-type recognition based on clustered data. Full article

The inflammatory response plays a central role in the pathophysiology of various chronic diseases such as periodontitis, type 2 diabetes mellitus (T2DM), and coronavirus disease 2019 (COVID-19), whose coexistence is associated with an increase in clinical complications and a more severe and serious course of these diseases. Current evidence on the interrelationship between periodontitis, T2DM, and COVID-19 remains insufficient, highlighting the need for further research to elucidate these associations. The main aim of this narrative review is to provide the current landscape of the most relevant aspects of the interrelationship between periodontitis, T2DM, and COVID-19. This narrative review was carried out through a specialized, exhaustive, and structured search of published studies indexed in the electronic databases PubMed and LILACS, for the inclusion of studies in English and Spanish, respectively, without date restriction. A search strategy was performed using the Boolean operators AND, OR, and NOT, with the following DeCS/MeSH terms: “periodontal disease”, “periodontitis”, “type 2 diabetes mellitus”, “SARS-CoV-2”, and “COVID-19”. A variety of articles were included, focusing on the most relevant aspects of the interrelationship between periodontitis, T2DM, and COVID-19. Findings suggest that inflammation is a unifying mechanism, which leads to the severity of these conditions through four shared axes: (1) a clinicopathological axis involving systemic manifestations; (2) an axis associated with metabolic alterations linked to glycemic dysregulation; (3) an axis related to enzyme overexpression linked to altered angiotensin-converting enzyme (ACE)-2 expression and glucose metabolism; and (4) an inflammatory axis. These synergistic interactions can cause these three diseases to mutually enhance each other, creating a vicious cycle, worsening the patient’s health. Full article

Background and Clinical Significance: Arterial and venous thromboses are typically distinct clinical entities, each governed by unique pathophysiological mechanisms. The concurrent manifestation of both, particularly in the setting of massive pulmonary embolism (PE), is exceptionally rare and poses significant diagnostic and therapeutic challenges. Case Presentation: This report describes a 61-year-old male with well-controlled hypertension and type 2 diabetes who developed extensive thromboses involving deep vein thrombosis (DVT) of the right popliteal vein, arterial thrombosis of the left iliac artery, and massive PE. The patient was initially managed conservatively, in accordance with the European Society of Cardiology (ESC) 2019 Guidelines for Acute PE, using unfractionated heparin (UFH), low-molecular-weight heparin, a direct oral anticoagulant (DOAC), and adjunctive therapy. This approach was chosen due to the absence of hemodynamic instability. However, given failed percutaneous revascularization and persistent arterial occlusion, surgical thromboendarterectomy (TEA) was ultimately required. Post hoc genetic testing was prompted by the complex presentation in the absence of classical provoking factors—such as trauma, surgery, malignancy, or antiphospholipid syndrome—consistent with recommendations for selective thrombophilia testing in atypical or severe cases. The analysis revealed four thrombophilia-associated polymorphisms: heterozygous Factor V Leiden (FVL; R506Q genotype), Plasminogen Activator Inhibitor-1 (PAI-1; 4G/5G genotype), Methylenetetrahydrofolate reductase (MTHFR; c.677C > T genotype), and homozygous Angiotensin-Converting Enzyme Insertion/Deletion (ACE I/D; DD genotype). Conclusions: While each variant has been individually associated with thrombotic risk, their co-occurrence in a single patient with simultaneous arterial and venous thromboses has not, to our knowledge, been previously documented. This case underscores the potential for gene–gene interactions to amplify thrombotic risk, even in the presence of variants traditionally considered to confer only modest to moderate risk. It highlights the need for a multidisciplinary approach and raises questions regarding pharmacogenetics, anticoagulation, and future research into cumulative genetic risk in complex thrombotic phenotypes. Full article

Traditional LLC resonant converters face significant challenges in wide-output-voltage-applications, such as limited voltage gain, efficiency degradation under wide-gain range, and increased complexity in magnetic component design. For example, in electric vehicle charging power modules, achieving wide output voltage typically relies on changing the transformer turns ratio or switching the series-parallel circuit configuration via relays, which prevents real-time dynamic adjustment. To overcome these limitations, this paper proposes a wide-gain-range control method based on a full-bridge T-type three-level LLC resonant converter, capable of achieving a voltage gain range exceeding six times. By integrating a T-type three-level bridge arm with PWM modulation and employing a variable-topology and variable-frequency control strategy, the proposed method achieves synergistic optimization for wide-output-voltage-applications. PWM modulation enables wide-range voltage output by dynamically adjusting both the converter topology and switching frequency. Finally, the proposed method is validated through circuit simulations and experimental results based on a full-bridge T-type three-level LLC converter prototype, demonstrating its effectiveness and feasibility. Full article