Polytechnic University of Timişoara

Unmanned aerial vehicles (UAVs) have enabled numerous inventive solutions to multiple problems, considerably facilitating our daily lives; however, UAVs frequently rely on an open wireless channel for communication, making them susceptible to cyber-physical threats. Also, UAVs cannot execute complicated cryptographic algorithms due to their limited onboard computing capabilities. Balancing high-security levels and minimum computation costs is imperative when developing a security solution for UAVs. Consequently, several proxy signature schemes have been proposed in the literature to fulfil these requirements. Nevertheless, many of these solutions face the issue of high computation costs, and some exhibit security vulnerabilities that could not be more feasible options for UAV communication. Considering these constraints in mind, in this article, we introduce an improvised certificate-based proxy signature scheme (ICPS), which leverages the concept of hyperelliptic curve cryptography (HECC) to meet the security and efficiency requirements of UAV networks. The proposed ICPS scheme offers a range of notable features, including its ability to address key escrow and secret key distribution issues. The proposed ICPS scheme's security hardness has been evaluated using the widely known security tool, the random oracle model (ROM), proving its resilience against known and unknown cybersecurity threats. Finally, this study conducts a performance comparison of the proposed scheme against existing schemes, emphasizing its outstanding cost-efficiency. Notably, the computation cost is measured at 5.3536 ms and the communication cost at 1120 bits, substantially lower than relevant existing schemes.

The paper studies the free vibration of carbon nanotube-reinforced composite (CNTRC) beams with variable cross-sections. The carbon nanotubes embedded in a polymeric matrix are assumed to be functionally graded (FG) across the beam’s thickness, with their material properties determined using the rule of mixtures. Various CNT distribution patterns and cross-sectional variation profiles are considered. The study employs Timoshenko beam theory, deriving the governing equations via Hamilton’s principle. These differential equations with variable coefficients are solved using the differential transform method (DTM), which is formulated as a unified eigenvalue problem applicable to various boundary conditions. The computed results are validated against available literature to ensure accuracy and reliability. Subsequently, a comprehensive parametric study examines the influence of geometrical and material parameters on the vibration behavior of FG-CNTRC beams. The findings reveal that natural frequencies are significantly affected by taper parameters, CNT content, and nanotube distribution patterns. Finally, the study identifies the CNT distributions that offer the most favorable vibration characteristics.

(1) Background: this study investigates the short-term effects of coenzyme Q10 (CoQ10) on mitochondrial respiration, fatty acid metabolism, oxidative stress gene expression, and sirtuin activity in young (passage 5, P5) and aged (passage 16, P16) mesenchymal stem cells (MSCs). (2) Methods: Mitochondrial respiration was assessed by measuring oxygen consumption after 24 h of treatment. Gas chromatography–mass spectrometry (GC-MS) analysis assessed cellular fatty acid methyl ester profiles. Quantitative polymerase chain reaction (qPCR) demonstrated the passage-dependent expression of oxidative stress-related genes and sirtuins in response to CoQ10 treatment. (3) Results: CoQ10 enhanced basal respiration and spare respiratory capacity (SRC), particularly in older senescent cells. CoQ10 improved basal respiration and ATP-linked oxygen consumption in young MSCs and partially restored these functions in aged MSCs. Moreover, CoQ10 increased saturated fatty acids, particularly in young cells, and decreased monounsaturated fatty acids in aged cells. qPCR analysis revealed passage-dependent modifications in oxidative stress-related genes and sirtuin expression; CoQ10 exposure significantly influenced SIRT1 and SIRT3 activity, leading to an increase in PPARγ and CAT expression. (4) Conclusions: these results highlight CoQ10’s potential to alleviate mitochondrial dysfunction and metabolic shifts associated with cellular aging, underscoring its therapeutic value for age-related mitochondrial and metabolic disorders.

Low-light image enhancement is an important task in computer vision, often made challenging by the limitations of image sensors, such as noise, low contrast, and color distortion. These challenges are further exacerbated by the computational demands of processing spatial dependencies under such conditions. We present a novel transformer-based framework that enhances efficiency by utilizing depthwise separable convolutions instead of conventional approaches. Additionally, an original feed-forward network design reduces the computational overhead while maintaining high performance. Experimental results demonstrate that this method achieves competitive results, providing a practical and effective solution for enhancing images captured in low-light environments.

The rapid evolution of financial markets and technological advancements has significantly impacted the field of accounting, creating a demand for innovative approaches to financial forecasting and decision making. Our research addresses contemporary socio-economic needs within the accounting domain, particularly the growing reliance on automation and artificial intelligence (AI) to enhance the accuracy of financial projections and improve operational efficiency and proposes a theoretical and empirical framework for applying neural networks to predict corporate profitability, using key accounting variables. The proposed model operates on two distinct levels. At the theoretical level, we defined the conceptual relationship between accounting constructs and profitability, proposing that shifts in financial metrics directly influence the net income. This relationship is grounded in established accounting theory and is operationalized through financial ratios and indicators, creating a clear, semantically linked framework. At the empirical level, these abstract concepts can be reified into measurable variables, where a multi-layered neural network can be deployed to uncover complex, nonlinear relationships between the input data and predicted profit. Through iterative training and testing, the model can provide plausible predictions, validated by historical financial data. We are taking time-honored accounting principles and combining them with cutting-edge technology to predict profitability in ways that have not been possible before. The hope is that by embracing this new approach, we can make financial predictions more accurate, support better strategic decision making, and, ultimately, help businesses navigate the complexities of modern financial markets. This research addresses the growing need for advanced financial forecasting tools by applying neural networks to accounting. By combining theoretical accounting principles with cutting-edge machine learning techniques, we aim to demonstrate that neural networks can bridge the gap between traditional accounting practices and the increasing demands for predictive accuracy and strategic decision making in a rapidly evolving financial environment.

We establish a sufficient condition for the existence of a nonuniform exponential dichotomy of an evolution family on the half-line in terms of evolution semigroups. Such endeavour is not at all of a formal type and our proof is new even in the particular case of uniform exponential dichotomy.

Reducing the ecological impact of dyes through wastewater discharge into the environment is a challenge that must be addressed in textile wastewater pollution prevention. Congo red (CR) dye is widely used in experimental studies for textile wastewater treatment due to its high organic loads used in its preparation. The degradation of organic dyes of the CR type was investigated using the photocatalytic activity of functionalized polymers. We have employed photodegradation procedures for both polymer-supported glycine groups (Code: AP2) and polymer-supported glycine-Zn(II) (Code: AP2-Zn(II)). A photocatalysis efficiency of 89.2% was achieved for glycine pendant groups grafted on styrene-6.7% divinylbenzene copolymer (AP2) and 95.4% for the AP2-Zn(II) sample by using an initial concentration of CR of 15 mg/L, a catalyst concentration of 1 g/L, and 240 min of photocatalysis. The findings provided here have shown that the two materials (AP2 and AP2-Zn(II)) may be effectively employed in the heterogeneous photocatalysis method to remove CR from water. From the perspective of the degradation mechanism of CR, the two photocatalysts act similarly.

The study explores the impact of floods, phenomena amplified by climate change and human activities, on the natural and anthropogenic environment, focusing on the analysis of a section of the Cigher River in the Crișul Alb basin in western Romania. The research aims to identify areas vulnerable to flooding under different discharge scenarios, assess the impact on agricultural lands, and propose a reproducible methodology based on the integration of GIS technologies, hydraulic modeling in HEC-RAS, and the use of LiDAR data. The methodology includes hydrological analysis, processing of the Digital Elevation Model (DEM), delineation of geometries, hydraulic simulation for four discharge scenarios (S1–S4), and evaluation of the flood impact on agricultural and non-agricultural lands. Evaluated parameters, such as water velocity and flow section areas, highlighted an increased flood risk under maximum discharge conditions. The results show that scenario S4, with a discharge of 60 m³/s, causes extensive flooding, affecting 871 hectares of land with various uses. The conclusions emphasize the importance of using modern technologies for risk management, protecting vulnerable areas, and reducing economic and ecological losses. The proposed methodology is also applicable to other river basins, representing a useful model for developing sustainable strategies for flood prevention and management.

Wireless Sensor Networks gradually became a mature technology that enabled the implementation of a large number of critical applications. However, the integration of such networks in much more complex systems, such as IoT, still poses a major challenge. In this paper we present a viable solution to accomplish such a difficult task by using MQTT-SN to integrate critical real-time WSNs into an IoT platform. The core of our work is a platform independent real-time driver for MQTT-SN along with a communication architecture to enable the integration of low end devices into an MQTT network using MQTT-SN. We also describe a comprehensive practical demonstration using real hardware modules that validates our claimed solution.

This study explores possible applications of AI technology in online journalism, given the predictions that speed and adaptation to the new medium will increase the penetration of automation in the production business. The literature shows that while the human supervision of journalistic workflow is still considered vital, the journalistic workflow is changing in nature, with the writing of micro-content being entrusted to ChatGPT-3.5 among the most visible features. This research assesses readers’ reactions to different headline styles as tested on a sample of 624 students from Timisoara, Romania, asked to evaluate the qualities of a mix of human-written vs. AI-generated headlines. The results show that AI-generated, informative headlines were perceived by more than half of the respondents as the most trustworthy and representative of the media content. Clickbait headlines, regardless of their source, were considered misleading and rated as manipulative (44.7%). In addition, 54.5% of respondents reported a decrease in trust regarding publications that frequently use clickbait techniques. A linguistic analysis was conducted to grasp the qualities of the headlines that triggered the registered responses. This study provides insights into the potential of AI-enabled tools to reshape headline writing practices in digital journalism.

The laser pyrolysis technique was used in the synthesis of magnetic iron oxide nanopowders in the presence of ethanol vapors as a sensitizer. This technique uses the energy from a continuous-wave CO2 laser operating at a 9.25 μm wavelength, which is transferred to the reactive precursors via the excited ethanol molecules, inducing a rapid heating of the argon-entrained Fe(CO)5 vapors in the presence of oxygen. For a parametric study, different samples were prepared by changing the percentages of sensitizer in the reactive mixture. Moreover, the raw samples were thermally treated at different temperatures and their morpho-structural and magnetic properties were investigated. The results indicated a high degree of crystallinity (mean ordered dimension) and enhanced magnetic properties when high percentages of ethanol vapors were employed. On the contrary, at low ethanol concentrations, due to a decrease in the reaction temperature, nanoparticles with a very low size were synthesized. The raw particles have a dimension in the range of 2.5 to 10 nm (XRD and TEM). Most of them exhibited superparamagnetic behavior at room temperature, with saturation magnetization values up to 60 emu/g. The crystalline phase detected in samples is mainly maghemite, with a decreased carbon presence (up to 8 at%). In addition to the expected Fe-OH on the particles surfaces, C (and O) bearing functional groups such as C-OH or C=O that act as a supplementary hydrophilic agent in water-based suspension were detected. Using the as-synthesized and thermally treated nanopowders, water suspensions without or with hydrophilic agents (CMCNa, L-Dopa, chitosan) were prepared by means of a horn ultrasonic homogenizer at 0.5 mg/mL concentrations. DLS analyzes revealed that some powder suspensions maintained stable agglomerates over time, with a mean size of 100 nm, pH values between 4.8 and 5.3, and zeta-potential values exceeding 40 mV. All tested agents greatly improved the stability of 250–450 °C thermally treated NPs, with L-Dopa and Chitosan inducing smaller hydrodynamic sizes.

Copper nanoparticles (CuNPs) have attracted attention due to their low cost and high specific surface area. In this work, a simple and inexpensive two-step synthesis method was proposed to prepare highly stable and well-dispersed spherical CuNPs in solution with a particle size of approximately 37 nm. Synthesis of CuNPs was carried on in the presence of complexing agent trisodium citrate (TSC), while for the chemical reduction step, sodium borohydride (NaBH4) was used. Taking into account the potential of this type of nanoparticles, their synthesis and characterization represent a current and relevant topic in the field. The ability to control the size, shape and properties of CuNPs by adjusting the synthesis parameters (pH, precursor:stabilizer:reductant ratio, homogenization time, temperature) offers extraordinary flexibility in the development of these materials. The combination of characterization techniques such as SEM, EDX, UV–Vis, Raman, FT-IR and AFM provides a thorough understanding of the structure and properties of CuNPs, allowing the modulation of the properties of the obtained nanoparticles in the desired direction. Based on the studies, the copper reduction mechanism was proposed. For the theoretical verification of the size of the experimentally obtained spherical CuNPs, Mie theory was applied. A stability study of the synthesized CuNPs in optimal conditions was performed using UV–Vis analysis at specific time intervals (1, 3, 30 and 60 days), the sample being kept in the dark, inside a drawer at 25 °C. The CuNPs obtained after setting the optimal synthesis parameters (Cu(II):TSC:BH4+ = 1:1:0.2, pH = 5, homogenization time 60 min and temperature 25 °C) were then tested to highlight their antibacterial effect on some reference bacterial strains. The obtained CuNPs demonstrated very good antimicrobial efficacy compared to traditional antimicrobials, for both Gram-negative and Gram-positive bacteria. This may reduce the development of antimicrobial resistance, an urgent medical issue. After evaluating the cytotoxic effects of CuNPs on the SKBR3 cancer cell line, a significant decrease in cell proliferation was observed at the 0.5 mg/mL concentration, with a reduction of 89% after 60 h of cultivation. Higher concentrations of CuNPs induced a more rapid cytotoxic effect, leading to an accelerated decline in cell viability.

The main goal of this study is to provide new q-Fejer and q-Hermite-Hadamard type integral inequalities for uniformly convex functions and functions whose second quantum derivatives in absolute values are uniformly convex. Two basic inequalities as power mean inequality and Holder’s inequality are used in demonstrations. Some particular functions are chosen to illustrate the investigated results by two examples analyzed and the result obtained have been graphically visualized.

This paper reports a miniature low-profile denim textile 2-port MIMO (multiple-input-multiple-output) antenna for dual-bands: 5G sub-6 3.5 GHz and Wi-Fi 5.2 GHz wearable applications. This MIMO antenna has impedance bandwidths and peak gain of 310 MHz and 8.3 dBi and 950 MHz 13.0 dBi at 3.5 and 5.2 GHz, respectively. This MIMO antenna has a compact area of 0.078 λ0², with both antenna elements of the MIMO being a modified elliptical patch, L-shaped stubs for impedance matching, and a circular decoupling ring to achieve > 25 dB port isolation. The designed antenna is very tiny and integrated into the shirt’s pocket. It is tested in two positions, i.e., hidden (integrated inside the pocket, for example, military applications) and visible (when integrated on the pocket surface for conventional communication). Moreover, the antenna’s working is analyzed in these positions (hidden and visible), and it was found that it functions well in both 5G sub-6 GHz and Wi-Fi frequency bands with nearly close gain values and communication range. This MIMO antenna has a very small ECC (envelope correlation coefficient) of 0.006/0.002 in both frequency bands, which shows high channel isolation. The 1 gm/10 gm SAR (specific absorption rate) values at 3.5 and 5.2 GHz are 0.034/0.057 and 0.026/0.0132 W/Kg, respectively, substantially lesser than the recommended values of FCC/ICNIRP.

With the proliferation of IoT-based applications, security requirements are becoming increasingly stringent. Given the diversity of such systems, selecting the most appropriate solutions and technologies to address the challenges is a complex activity. This paper provides an exhaustive evaluation of existing security challenges related to the IoT domain, analysing studies published between 2021 and 2025. This review explores the evolving landscape of IoT security, identifying key focus areas, challenges, and proposed solutions as presented in recent research. Through this analysis, the review categorizes IoT security efforts into six main areas: emerging technologies (35.2% of studies), securing identity management (19.3%), attack detection (17.9%), data management and protection (8.3%), communication and networking (13.8%), and risk management (5.5%). These percentages highlight the research community’s focus and indicate areas requiring further investigation. From leveraging machine learning and blockchain for anomaly detection and real-time threat response to optimising lightweight algorithms for resource-limited devices, researchers propose innovative and adaptive solutions to address emerging threats. The review underscores the integration of advanced technologies to enhance IoT system security, while also highlighting ongoing challenges. The paper concludes with a synthesis of security challenges and threats of each identified category, along with their solutions, aiming to support decision-making during the design approach of IoT-based applications and to guide future research toward comprehensive and efficient IoT frameworks.

Geopolymer concrete reinforced with MiniBars™ could be an eco-friendly, innovative, durable, high-strength material substitute for common Portland cement in buildings. AR glass fiber MiniBars™ composites (AR MiniBars™) (ReforceTech AS, Royken, Norway) 60 mm in length were utilized to strengthen the geopolymer matrix for the fabrication of unidirectional geopolymer composites reinforced by AR MiniBars™ (AR MiniBars™ FRBCs). New AR MiniBars™ FRBCs were fabricated by adding different amounts of AR MiniBars™ (0, 12.5, 25, 50, 75 vol.%) into the fly ash geopolymer paste. Geopolymers were obtained by combining fly ash powder with Na2SiO3/NaOH in a ratio of 2.5:1, which served as an alkaline activator. AR MiniBars™ FRBCs were cured for 48 h at 70 °C and tested for different mechanical properties. Fly ash, AR MiniBars™, and AR MiniBars™ FRBC were evaluated by optical microscopy and SEM. The addition of AR MiniBars™ increased the mechanical properties of AR MiniBars™ FRBCs. The mechanical properties of AR MiniBars™ FRBCs were heightened compared to the geopolymer without AR MiniBars™; the flexural strength was 18.80–30.71 times greater, the flexural modulus 4.07–5.25 times greater, the tensile strength 3.49–8.27 times greater, the force load at upper yield tensile strength 3.6–7.72 times greater, and the compressive strength for cubic samples 2.75–3.61 times greater. The fractured surfaces and sections of AR MiniBars™ FRBCs were inspected by SEM and optical microscopy analyses, and even though there was no chemical adhesion, we achieved a good micromechanical adhesion of the geopolymer to AR MiniBars™. These results obtained encouraged us to propose AR MiniBars™ FRBCs for application in construction.

This paper presents experimental results regarding the development of new alloys from the binary ZnCu and ternary ZnCuMg systems. The alloys had controlled chemical compositions and were annealed at 300 °C and 400 °C, with holding times of 5 h and 10 h, followed by air cooling. Mechanical properties (tensile strength, yield strength, elongation, and elastic modulus) were determined. Structural analysis conducted after different heat treatments revealed that homogenization transforms the dendritic structure into a granular structure with intergranular eutectic presence. Biodegradation behavior showed that the ternary alloy exhibits higher degradation rates than the binary alloy. Applying the homogenization heat treatment has a good influence on the binary alloy only, not on the ternary alloy. Our research shows that that the complex alloying of zinc with copper and magnesium may improve cavitation behavior, doubling both the MDEmax parameter and cavitation resistance expressed by Rcav.