Search Results (377)

As climate change concerns, urban congestion, and environmental degradation intensify, cities prioritise cycling as a sustainable transport option to reduce CO₂ emissions and improve quality of life. However, rampant bicycle theft and poor security infrastructure often deter daily commuters and tourists from cycling. This study explores how advanced security measures can bolster sustainable urban mobility and tourism by addressing these challenges. A mixed-methods approach is utilised, incorporating primary survey data from Slovenia and secondary data on bicycle sales, imports and thefts from 2015 to 2024. Findings indicate that access to secure parking substantially enhances users’ sense of safety when commuting by bike. Regression analysis shows that for every 1000 additional bicycles sold, approximately 280 more thefts occur—equivalent to a 0.28 rise in reported thefts—highlighting a systemic vulnerability associated with sustainability-oriented behaviour. To bridge this gap, the study advocates for an innovative security framework that combines blockchain technology and Non-Fungible Tokens (NFTs) with encrypted Quick Response (QR) codes. Each bicycle would receive a tamper-proof QR code connected to a blockchain-verified NFT documenting ownership and usage data. This system facilitates real-time authentication, enhances traceability, deters theft, and builds trust in cycling as a dependable transport alternative. The proposed solution merges sustainable transport, digital identity, and urban security, presenting a scalable model for individual users and shared mobility systems. Full article

Ensuring the safety and quality of perishable agrifood products throughout the supply chain is essential. Key parameters, such as temperature and humidity, must be consistently monitored to prevent spoilage, maintain nutritional value, and minimise health risks. Fluctuations in transportation conditions can compromise product integrity, leading to deterioration and an increased risk of foodborne illness. Monitoring agrifood supply chains is essential, from packaging to last-mile delivery. Distribution methods that rely on non-automated monitoring systems, such as manual temperature measurements, are error-prone due to the failure of manual treatments and increase the likelihood of product deterioration. Emerging sensor technologies and the rapid development of Information and Communication Technologies offer new possibilities for real-time tracking, enabling stakeholders to maintain optimal conditions and monitor aesthetic, physicochemical, and nutritional quality. This paper proposes a cost-effective temperature and humidity traceability system that utilises wireless sensor networks (WSN) and Internet of Things (IoΤ) services to monitor perishable products within the agrifood supply chain ecosystem. It also provides an overview of recent innovations in sensor technologies, along with food quality indicators relevant to real-time monitoring of food quality. The proposed research examines the available sensor technologies and methodologies that enable continuous monitoring of agrifood supply chains. Moreover, the paper presents a pilot full-scale project from both functional and technological perspectives. Full article

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive software solution that automates metallographic analysis using advanced computer vision and deep learning models. Specifically, HawkEye software dynamically adapts its processing workflow based on the input image and its typological classification. The software supports both etched and non-etched specimens and automates the segmentation and classification of graphite nodules, gathering their morphological descriptors; it identifies microstructural phases and provides a global quality assessment. All these functions are embedded into a user-friendly interface designed for both laboratory and industrial use. Nevertheless, the key contribution of this work is the replacement of subjective evaluation with a reproducible, AI-driven approach, which significantly enhances the objectivity, traceability, and scalability of metallurgical analysis. In fact, the proposed approach achieves 99% accuracy in nodule classification compared to manual expert assessment, reduces manual image processing steps, and introduces a novel method for ferrite/perlite measurement in combination with carbide detection using YOLO and SAM models. Full article

Apparent power and power factor are crucial metrics for evaluating the energy transmission efficiency and reactive power management in power systems. The increasing complexity of power load structures, driven by evolving energy production and consumption models, has intensified the nonlinear and unbalanced characteristics of circuits, presenting significant challenges to accurate apparent power measurement. The IEEE 1459-2010 standard introduces the concept of effective apparent power to enhance the assessment of energy transmission efficiency under non-sinusoidal and unbalanced conditions. However, the absence of a physical standard and a standardized traceability method for effective apparent power results in inconsistent measurement outcomes across instruments. This study proposes a novel method to trace effective apparent power measurements to the International System of Units (SI) benchmarks, based on the loss characteristics of transmission lines. The method includes a comprehensive analysis of measurement uncertainty. Simulation and experimental validation confirm that the proposed traceability circuit can achieve a measurement uncertainty of 0.0110% (coverage factor k = 2), satisfying the engineering requirement of expanded uncertainty U approximately 0.02% (k = 2). These results demonstrate the method’s practical suitability for engineering applications. Full article

This report analyzes the different standard methods of quantity measurement, which, when applied in the processes of receiving and transferring fuel quantities, lead to discrepancies and accounting losses. Three main factors contribute to these discrepancies: unavoidable errors of measuring devices (calibration uncertainty ranging from 0.1 to 0.5% at best), systematic errors due to non-applied corrections during transactions, and systematic errors due to different regulations, which result in inconsistent conversion rules applied throughout the entire purchase-production-sales chain. Modeling of air buoyancy effects showed that neglecting buoyancy correction can lead to measurable and economically significant discrepancies, especially in large-scale operations. The mass of light petroleum products can be underestimated by up to 0.15%, potentially resulting in approximately $3 million in annual financial losses for a medium-sized refinery processing 10,000 tonnes per day. These findings underscore the necessity of applying buoyancy corrections for conventional weighing, especially for liquid petroleum products (LPP) measured in open systems. Conversely, for LPG weighed in closed, pressurized containers, a constant correction factor (0.99985) applies, but its economic impact is negligible. Therefore, the study recommends omitting this LPG correction unless contractually required, to streamline processes and reduce complexity. Achieving result comparability throughout the entire petroleum supply chain requires implementing uniform quantity calculation provisions using calibrated instruments and standardized methods under different conditions. This necessitates that all measurement results are traceable to reference conditions (mass in vacuum, volume at +15 °C). The proposed algorithms for oil mass and volume measurement and recalculation highlight the need for unified international regulations and a robust system. Full article

Matrix certified reference materials (mCRMs) are materials characterized by suitable homogeneity, stability, and traceability, with certified values, including uncertainties, and a specific matrix. mCRMs constitute a reference for instrumental analytical methods and ensure their metrological consistency. Matrix certified reference materials (mCRMs) are essential tools for ensuring the accuracy and traceability of analytical measurements, particularly for samples with complex matrices. These mCRMs are carefully manufactured materials that closely mimic the composition and properties of real samples, allowing laboratories to validate their analytical methods, calibrate analytical instruments, or check the classical methods. This article highlights the challenges associated with the production and characterization of these complex mCRMs, including obtaining homogeneous materials, establishing accurate target values, and ensuring stability for different types of materials, such as gases, liquids, and metal alloys. Additionally, the process of statistical evaluation through the use of advanced statistical methods is discussed, as is the systems approach associated with the implementation of the ISO 17034 standard, which specifies the requirements for manufacturers of reference materials. This paper also includes a summary of the current status in trends of normalization as well as mCRM production. Full article

This study proposes a memory-based forensic procedure for real-time recovery of deleted data in Microsoft SQL Server environments. This approach is particularly relevant for sensor-driven and embedded systems—such as those used in IoT gateways and edge computing platforms—where lightweight SQL engines store critical operational and measurement data locally and are vulnerable to insider manipulation. Traditional approaches to deleted data recovery have primarily relied on transaction log analysis or static methods involving the examination of physical files such as .mdf and .ldf after taking the database offline. However, these methods face critical limitations in real-time applicability and may miss volatile data that temporarily resides in memory. To address these challenges, this study introduces a methodology that captures key deletion event information through transaction log analysis immediately after data deletion and directly inspects memory-resident pages loaded in the server’s Buffer Pool. By analyzing page structures in the Buffer Pool and cross-referencing them with log data, we establish a memory-driven forensic framework that enables both the recovery and verification of deleted records. In the experimental validation, records were deleted in a live SQL Server environment, and a combination of transaction log analysis and in-memory page inspection allowed for partial or full recovery of the deleted data. This demonstrates the feasibility of real-time forensic analysis without interrupting the operational database. The findings of this research provide a foundational methodology for enhancing the speed and accuracy of digital forensics in time-sensitive scenarios, such as insider threats or cyber intrusion incidents, by enabling prompt and precise recovery of deleted data directly from memory. These capabilities are especially critical in IoT environments, where real-time deletion recovery supports sensor data integrity, forensic traceability, and uninterrupted system resilience. Full article

This paper presents a Maxwell–Wien bridge for use in the calibration of standard inductances with values between 100 µH and 10 H and frequencies from 20 Hz to 20 kHz. The inductances are measured by comparison with a variable standard capacitor, in parallel association with a variable standard resistor, on the bridge modified by a Wagner balance. The variable standards are calibrated after the bridge balance. The other resistors in the bridge are standard resistors, pre-calibrated in AC using an automatic Wheatstone bridge and in DC after the bridge has been balanced using a comparison bridge with standard resistors traceable to the quantum Hall effect standards. PXI modules are used to supply the bridge with two voltages controllable in amplitude and phase. Design details and the uncertainty budget are discussed. For an inductance of 100 mH characterized by an internal resistance of 83 Ω, the expanded uncertainties are less than 6 µH on the inductance and 20 mΩ on the internal resistance. For inductances from 100 µH to 10 H, the relative uncertainties are less than 0.02% of the inductance and 0.2% of the internal resistance from 20 Hz to 20 kHz. Full article

Vehicle identification number (VIN) reappearance technology is an important means of vehicle traceability in various criminal cases. However, with the advancement of metallurgical techniques, the corrosion resistance of metal becomes stronger, and the traditional chemical etching reappearance method gradually fails. In order to break through the dilemma of traditional methods, this study establishes an electrochemical corrosion system by introducing the corrosion inhibitor hexamethylenetetramine (HMTA) to precisely regulate the electrochemical dissolution kinetics. Material characterization and electrochemical measurements demonstrated that the selective adsorption of HMTA significantly enhances the potential difference between plastically deformed regions and the normal metal substrate (ΔE_max = 6 mV). By effectively suppressing the corrosion rate in non-target areas, HMTA promotes selective anodic oxidation reactions in the vehicle identification number character regions due to their distinct microstructural characteristics, thereby substantially improving the contrast of the reappeared VIN markings. Density functional theory calculations and molecular dynamics simulations further reveal the formation of a dense adsorption layer, which is a key factor in improving the reproducibility of the results. The experimental results demonstrate that under conditions of 6 V applied voltage, with 0.5 M hydrochloric acid and 0.02–0.03 M HMTA in the electrolyte, efficient VIN reappearance could be achieved within 3–4 min on filed-down surfaces. Full article

Circular economy marketing (CEM) represents an innovative approach to aligning business strategies with sustainability objectives. This paper explores the role of CEM as a driver of green marketing innovation, emphasising strategies that minimise environmental impact on business competitiveness while enhancing consumer engagement. Using a systematic literature review based on the PRISMA methodology, we identified 39 high-impact studies across multiple industries, categorising findings into key themes, theoretical frameworks, and marketing strategies. The analysis highlights emerging trends, including the shift toward product-service systems (PSSs), behavioural nudging, transparent sustainability branding, and integration of digital technologies such as AI and blockchain to enhance traceability and consumer trust. Findings reveal that while circular economy marketing presents opportunities for businesses to differentiate themselves and build long-term sustainability strategies, significant challenges remain, including scalability issues, consumer scepticism, and risks of greenwashing. Moreover, gaps in standardising impact measurement and industry-specific adaptation hinder wider implementation. Business model innovation, policy support, and collaborative efforts are crucial in overcoming these barriers. This study provides insights for businesses, policymakers, and researchers, highlighting how CEM fosters green innovation and competitiveness. Future research should compare the effectiveness of various strategies to accelerate the transition toward sustainable marketing practices through regulation and interdisciplinary collaboration. Full article

Metrological traceability is essential for ensuring the accuracy of measurement results and enabling a comparison of results to support decision-making in society. This paper explores a structured approach to modelling traceability chains, focusing on the role of residual measurement errors and their impact on measurement accuracy. This work emphasises a scientific description of these errors as physical quantities. By adopting a simple modelling framework grounded in physical principles, the paper offers a formal way to account for the effects of errors through an entire traceability chain, from primary reference standards to end users. Real-world examples from microwave and optical metrology highlight the effectiveness of this rigorous modelling approach. Additionally, to further advance digital systems development in metrology, the paper advocates a formal semantic structure for modelling, based on principles of Model-Driven Architecture. This architectural approach will enhance the clarity of metrological practices and support ongoing efforts toward the digital transformation of international metrology infrastructure. Full article

Background: Silver–Russell syndrome (SRS) is a genetic disorder characterized by prenatal and postnatal growth retardation. Affected individuals commonly present with low birth weight, intrauterine growth restriction, postnatal short stature, hemihypotrophy, characteristic facial features, and body asymmetry. Methods: This study includes 24 Taiwanese children with SRS aged 2 years to 13 years and 3 months who were recruited at MacKay Memorial Hospital and other Taiwan hospitals between January 2013 and December 2024. Functional independence was assessed using the Functional Independence Measure for Children (WeeFIM) to evaluate self-care, mobility, and cognition domains. Results: The mean total WeeFIM score was 106.9 ± 23.2 (range: 54–126), with mean self-care, mobility, and cognition scores of 44.4 ± 13.8 (maximum 56), 32.4 ± 5.1 (maximum 35), and 30.2 ± 6.0 (maximum 35), respectively. The results of the restricted cubic spline analysis reveal a clear positive linear correlation before school age (approximately 72 months), followed by a plateau (p for nonlinearity < 0.05). Traceable molecular data were available for thirteen participants, of whom nine (69%) had loss of methylation at chromosome 11p15 (11p15LOM), and four (31%) had maternal uniparental disomy of chromosome 7 (upd(7)mat). Of the 24 children, 46% required assistance with bathing, which was strongly correlated with self-care ability and body height. In contrast, most of the children had independence in mobility tasks such as walking and stair climbing. However, some required support in cognitive tasks, including problem-solving, comprehension, and expression. Overall, the included children reached a functional plateau later than the normative population, with the greatest delays in self-care and mobility domains. Conclusions: This study highlights that Taiwanese children with SRS require support in self-care and cognitive tasks. Functional independence in self-care and mobility domains was positively associated with body height. The WeeFIM questionnaire effectively identified strengths and limitations, emphasizing the need for individualized support in daily activities. Full article

The complexity of tracing foodborne pathogens in the food chain has increased significantly due to the long and complicated chain, the involvement of numerous links, and the presence of various types of pathogens at different stages and environments. Traditional typing techniques are not sufficient to meet the requirements of tracing pathogens in the food chain. Whole-Genome Sequencing (WGS) has gradually become an important technological tool for characterizing and tracing pathogens in the food chain due to comprehensive information, speed, and superior discriminatory power. This paper provides an overview of the advantages of WGS and its application in foodborne pathogen traceability. This paper focused on foodborne pathogen contamination pathways during the processing of animal foods in commercial restaurant kitchens and the potential contamination of milk, milk powder, and other dairy products by pathogens during processing in the dairy industry chain and environments. Improper handling practices during meat processing (i.e., using cloths, washing hands without soap, and cleaning boards with knives) were a critical point of foodborne pathogen cross-contamination in commercial kitchen premises. However, in dairy products, contamination of pathogens in raw milk was the main cause of foodborne disease outbreaks. Therefore, preventing the contamination of pathogens in food should not only be focused on hygiene measures during processing and in environments but also on the quality and hygiene of raw materials to prevent the spread of foodborne pathogens throughout the entire production chain. Further, Whole-Metagenome Sequencing and DNA sequence markers are considered to be the future direction of WGS. The purpose of this work is to promote the wider application of WGS during the processing of meat and dairy products and provide theoretical support for the rapid investigation and accurate traceability of foodborne pathogen outbreaks in food. Full article

This paper aims to define a model for measuring the localness of a company in an innovative and reliable way, motivated by the growing consumer interest in purchasing local products and supporting local economies. The proposed Expenses Localness Indicators (ELI) model uses existing data from information systems to define Localness Indicators, and incorporates Localness Levels based on geographic and economic criteria. It can be applied to any type of financial entity and overcomes the difficulty of defining localness in e-commerce companies or digital businesses in general. Previous studies have examined the impact of localness and investigated its effectiveness as a branding strategy for managers, mainly through product traceability. The ELI model uses as data the expenses of a company paid to other financial entities. The Expenses Localness Indicators are determined based on the distribution of these payments combined with the localness of the paid financial entities. These Indicators represent the degree of localness as a percentage, ranging from 0% (non-local) to 100% (fully local), and may vary over time. The results of the presented examples indicate that a company’s localness increases as it spends more of its expenses on local financial entities and vice versa. Specific strategies have been tested using synthetic data that demonstrate the correct functioning of the model’s indicators. The ELI model could be used to provide reliable and certifiable information to consumers who want to know where their money goes when they buy products. Implementing the proposed model on a large scale would require acceptance by as many companies and states as possible. However, by making the necessary adjustments, the model could be applied on a smaller scale, supported by consumers and local governments interested in uncovering knowledge about localness. It could also be established as a valid indicator of localness to provide information that researchers, government agencies and professionals can use to promote local entrepreneurship. Full article

Calibration is crucial in quantitative analysis, ensuring the traceability of standards for an accurate comparison of results. In mercury determinations, a gas calibrator unit containing liquid mercury is used for calibration by injecting headspace volumes via syringe. The Dumarey equation has been used for over 35 years to calculate mercury headspace concentration, aligning closely with saturated vapor pressure equations. However, the 2006 Huber equation yields different values, creating discrepancies. This paper compares calibrations using the Dumarey equations against NIST 3133 certified reference material, with detection by a cold vapor atomic fluorescence spectrophotometer (CV-AFS). The gas standard was injected directly, while Hg^II in NIST 3133 was reduced to Hg⁰ and captured on gold traps. Across 10–24 °C, the Hg⁰ concentration was determined, with uncertainties ranging from 2.9% to 8.4% for a coverage factor of two. No significant differences were found between calibrations using NIST 3133 and the Dumarey equation. These findings provide crucial insights into the traceability and accuracy of mercury calibration methods, ensuring the reliability of measurements used for environmental monitoring and regulatory compliance. Full article