Polytechnic University of Timişoara

Numerous applications from electrical engineering and mechanical structures are mathematically modeled using dynamical systems theory. Our paper concerns the behaviors of a 3D dynamic system in terms of damped or periodical oscillations and asymptotic representation, considering the dependence on three physical parameters. This system is explicitly integrated via a smooth-function solution of a third–order nonlinear differential equation, which means that the obtained exact parametric solutions describe a heteroclinical orbit. The modified Optimal Parametric Iteration Method (mOPIM) is used to study the influence of the physical parameters. The advantages of the applied method include the small number of iterations due to due to the appropriate choice of auxiliary convergence control functions. The mOPIM solutions are in good agreement with the corresponding numerical results and this aspect is highlighted qualitatively by figures and quantitatively by tables, respectively, in this work. The accuracy of the obtained solutions is assessed via a comparison with the OPIM method and the iterative solutions using 5–8 iterations, via an iterative method. A qualitative analysis of errors is performed.

Identifying in-vehicle electronic control units based on voltage characteristics has been the subject of extensive research in cybersecurity. However, the results reported so far generally depend on restricted datasets and supervised learning. In this work, we show that clustering, i.e., unsupervised learning, of voltage characteristics, is in fact more challenging when done on a larger pool of electronic control units as several out-of-the-box clustering methods and metrics will fail to determine the correct number of clusters when exerted over a large dataset. To overcome this issue, we propose a new methodology that takes advantage of domain-specific constraints, which guide the search toward the correct number of electronic control units in a car, or even in a larger pool of units from several cars. We introduce two new metrics: correctness, which measures the success ratio with respect to the constraints, and divergence, which measures the consistency of the clustering, and show that they provide a strong indication for the optimal number of clusters. In this specific context, both metrics prove to be more reliable than the widely used Silhouette score, Davies-Bouldin and Calinski-Harabas indexes. We successfully test our methodology on the largest dataset available today for in-vehicle voltage characteristics and discover new insights regarding the number of devices.

This paper describes the development of several software-based games using a high-level programming language (C in our case), designed so that they can be ported to a Field-Programmable Gate Array (FPGA). It also outlines the mathematical foundations underlying these games. Making executables portable in this way can simplify running applications on FPGA platforms. Porting a game to an FPGA serves as evidence that arbitrary executables can be migrated to such hardware. The complete workflow for creating the game, along with the final game outcomes, is detailed in this paper. In addition, statistical analyses of these games were conducted. The proposed approach relies on graphics and character-handling libraries typically available in advanced programming languages. The background of this work is that a microcontroller architecture which can easily be run on a Spartan-6 FPGA was needed. The innovative point of this paper is that it created the cross-compilation toolchain on an uncommon microcontroller architecture, like the OpenRISC.

• Introduces CircularB-DfC, a design-stage framework for assessing and prioritising circularity in buildings • Integrates 35 circularity indicators and 20 enabling factors across design and value-chain processes • Provides Delphi-weighted scoring and a practitioner-oriented Excel tool for decision support • Demonstrates framework applicability through three contrasting regional and structural scenarios • Reveals how design strategies and enabling conditions jointly shape circular performance Circularity is increasingly recognised as a critical paradigm for sustainability in the built environment, yet existing efforts to assess it—whether focused on material flow analysis, design-for-disassembly strategies, durability metrics, or carbon accounting—remain fragmented and operate at different scales. Despite numerous indicator sets, the literature lacks an integrated framework that combines both technical design factors and the enabling organisational conditions required to support circular outcomes at the building level. This paper introduces CircularB-DfC (CircularB COST Action – Design for Circularity), a decision-Support Tool with a structured matrix for prioritising building design factors to enhance circular Material flows. The framework consolidates insights from a systematic literature review and a multi-stage expert engagement process, resulting in 35 technical indicators and 20 enabling factors . These are organised into four technical categories: Material Selection; Design for Disassembly; Embodied Energy and Carbon Footprint; Waste Minimisation, and one enabling category, Circular Construction Management, including Governance, Certification, Stakeholder Engagement, Digitalisation, and Socio-economic aspects. Indicators and enablers are aggregated into a Design Score and an Enabler Score to support early decision-making. The tool was applied to three illustrative scenarios: a reinforced-concrete industrial hall in the Western Balkans, a steel office building in Central Europe, and a timber residential project in East London. The steel scenario achieved the highest Design and Enabler Scores, the concrete scenario performed strongest in Waste Minimisation through prefabrication and site-based strategies, and the timber scenario scored lowest overall due to limited reuse and disassembly provisions in the original design. While CircularB-DfC offers a simple and transparent basis for integrating circularity in design, it is limited by the subjectivity of expert-based weighting and its static structure. Future research will focus on dynamic modelling, integration with digital tools, and broader validation to enhance applicability.

Melissa officinalis L. (lemon balm) is a Lamiaceae species widely used in traditional and contemporary herbal practice, yet its reported bioactivities are strongly preparation-dependent, reflecting variability between polyphenol-rich extracts and volatile essential-oil fractions. This integrative review links phytochemistry with recent preclinical findings and available clinical evidence. Across model systems, lemon balm most consistently shows antioxidant and anti-inflammatory signatures, with additional domain-specific signals reported in neurobehavioral, cardiometabolic, gastrointestinal, and dermatological models; however, comparability is limited by heterogeneous plant parts, extraction procedures, and chemical standardization. Preclinical findings were organized by biological domain, whereas clinically, the most consistent signals are observed for symptom-oriented endpoints, particularly anxiety/stress and sleep-related outcomes reported in controlled trials, including aromatherapy studies, while evidence for other indications remains mixed or insufficiently confirmed. Overall, the evidence supports continued development of chemically characterized, standardized preparations and mechanism-informed trials with harmonized outcomes and robust safety reporting to improve translational interpretability.

Natural and human-made disasters threaten cities increasingly, thus requiring a combination of disaster risk reduction and sustainable development strategies. Although vulnerability assessment methods and urban sustainability policies have improved significantly, these two fields remain separate, leading to fragmented policies that may work against resilience objectives. This paper provides an overview by conducting a systematic review of 87 peer-reviewed studies published between 2000 and 2024 that describe and analyze the intersection of disaster prevention policies and sustainability practices in urban planning. Thematic analysis was employed, and five major themes were revealed: policy implementation frameworks, climate adaptation strategies, preparedness mechanisms, vulnerability assessment approaches, and sustainability evaluation systems. The findings reveal a critical disconnect: on the one hand, vulnerability assessments highlight the structural–technical aspect and, at the same time, ignore the sustainability indicators (resource efficiency, social equity, and ecosystem services), while on the other hand, sustainability frameworks deliberately shut out disaster risk awareness from the core evaluation criteria. This methodological separation produces policy conflicts where disaster interventions may compromise environmental goals, and sustainability initiatives may increase hazard vulnerability. This review concludes that resilient cities require assessment methodologies synthesizing disaster risk and sustainability dimensions. A novel conceptual integration framework is suggested that combines hazard-exposure-vulnerability analysis with environmental–social–economic sustainability pillars, thus laying the groundwork for future operational tools. This joint viewpoint accepts that hazards mainly affect development that is not sustainability-oriented, while sustainable systems through adaptive design and equitable resource distribution inherently lower the vulnerability.

Abstract A strategy is proposed to determine the concentrations of components of pyranine, a cosmetic dye, to batch certification by the U.S. Food and Drug Administration. The main component of pyranine is mainly accompanied by two impurities during its synthesis. Harmful impurities were present at significantly lower concentrations than the main component. Despite the high degree of spectral overlap between the two impurities, specific spectral characteristics were exploited to overcome this challenge and determine their concentrations. The proposed method takes advantage of two key spectral peculiarities of the pyranine system: (1) the main component exhibits significant absorption at 404 nm where the impurities have negligible absorbance, and (2) despite being minor components, show intensely strong UV-vis spectra at concentrations comparable to those obtained in pyranine synthesis, facilitating their detection even at low concentrations. These characteristics enabled the development of a two-stage spectrophotometric approach. First, the concentration of the main dye was determined independently of the presence of the other two dyes in the ternary mixture using a direct absorbance method. Subsequently, the concentrations of the two impurities were determined by bivariate spectral calibration at two selected wavelengths. The results obtained by the proposed method were comparable to those obtained using other methods, such as HPLC and TLC. The proposed method is simple and accurate and can be used in quality control for the certification of dye batches. However, it critically depends on the unique spectral characteristics of the pyranine system, in particular the negligible absorption of the impurities at 404 nm and their relatively high absorption intensity comparable to main dye.