Search Results (3,075)

The structure, functionality, nutritional value, and sensory properties of food are significantly influenced by interactions between proteins and carbohydrates. These interactions occur through hydrogen bonding, electrostatic forces, hydrophobic interactions, and, in many cases, the covalent attachment of sugars to proteins via the Maillard reaction. High starch content in food matrices promotes interactions between proteins and starch components such as amylose and amylopectin, affecting gelation, retrogradation, and thickening. These interactions improve shelf stability and product quality. Additionally, protein–carbohydrate interactions regulate nutrient digestibility and glycemic response, playing a crucial role in the development of functional foods for diabetes and weight management. In silico studies have demonstrated that dietary fibers like pectin and cellulose can improve water retention and textural properties in processed meat products. Furthermore, processing techniques such as enzymatic hydrolysis, fermentation, pulsed electric fields (PEF), and low-temperature drying have been found to improve the functional properties and shelf life of food products. This review synthesizes recent findings on protein–carbohydrate interactions and highlights their potential in creating healthier, more appealing, and sustainable foods that align with modern consumer preferences. Full article

Determining the 3D position of a vehicle from a 2D image plays a key role in video surveillance, autonomous driving, and spatial localization. However, localization accuracy can significantly degrade in conditions of incomplete or synthetic measurement noise and keypoint jitter. In this paper, we propose a new iterative 3D position estimation algorithm (KGA). This algorithm includes geometric correction and calibration steps for converting from 2D to 3D coordinates; trajectory prediction and correction using a Kalman filter; and adaptive tuning of the filter parameters using the Goldschmidt algorithm. Experiments confirm that KGA outperforms the standard (FK) and modified (MFK) Kalman filters in accuracy and convergence speed, demonstrating robustness to various camera angles and noise levels. The novelty of this approach lies in the integration of the Goldschmidt algorithm into the Kalman filter to create an adaptation mechanism that dynamically adjusts the measurement noise covariance based on instantaneous innovation magnitude. Unlike end-to-end deep learning trackers or nonlinear filters (EKF/UKF), KGA is designed as a lightweight post-processing stage that can be seamlessly integrated into existing detection pipelines while maintaining the low computational footprint required for UAV-based edge deployment. The algorithm is of practical value for computer vision systems requiring accurate and robust tracking under varying observational conditions, with current implementation suitable for offline or buffered processing, and clear pathways to real-time deployment through code optimization. The algorithm is of practical value for computer vision systems requiring accurate and robust tracking under varying observational conditions. Full article

The Ethics Session of the International Primary Immunodeficiency Congress (IPIC), held in November 2025 and organised by the International Patient Organisation for Primary Immunodeficiencies (IPOPI), examined one of the most challenging developments emerging from genomic-enhanced newborn screening: the identification of serious, non-treatable disorders as incidental detection in programmes originally designed to detect severe combined immunodeficiency (SCID). Using a fictionalised clinical scenario based on the recent literature, the session explored the early diagnosis of ataxia–telangiectasia (AT) detected through TREC-based screening. The discussion highlighted the clinical value and psychological risks associated with presymptomatic detection, the persistent shortcomings in parental consent processes, the systemic pressures created by expanding genomic testing, and the ethical challenges surrounding the reporting and management of incidental findings in screening. The debate underscored the need for internationally coordinated frameworks to guide the management of incidental detection in newborn screening as genomic technologies become more deeply embedded in routine public health practice. Full article

Sustainable building practices can reduce environmental harm and support resilient urban development. To aid built-environment professionals such as architects, building scientists and planners in accomplishing regenerative design objectives, a variety of building rating and accreditation schemes have been developed, such as Greenstar or the Living Building Challenge. These schemes primarily focus on sustainability targets, such as energy and water use. Biodiversity considerations, despite their importance for ecosystem services and human health, are predominantly absent as core objectives in the building rating tools currently in use. To address this gap, we introduce the New Zealand Biodiversity Factor—Building (NZBF-B), a tool created to educate and incentivise the integration of biodiversity into buildings by assessing their biodiversity value, with a focus on prioritising native species. We outline the development of the NZBF-B, including its components, its scoring methodology, and an expert-informed weighting process used to determine the ecological relevance of each category. The tool captures key characteristics of building-associated biodiversity through measurable indicators that reflect both habitat provision and opportunities to strengthen human–nature connection. We advocate for the use of the NZBF-B alongside existing certification schemes to achieve more effective green building performance outcomes related to biodiversity. Full article

Background: This paper presents the development of digital tools created within the BIORADAR European project to improve user access to Life Cycle Assessment (LCA) results from the project’s use cases and to enable users to upload, benchmark and analyze their own data. The work addresses common challenges in circularity and environmental impact assessment, particularly data availability and expert-assisted self-assessment for users such as small- and medium-sized enterprises. Methods: The LCA data for the project use cases is calculated using the Environmental Footprint methodology. Benchmarking compares bio-approach use cases with traditional approaches across three key sectors selected by the BIORADAR project: fertilizer, textile and packaging. These sectors are recognized by the European Commission as three of the most important sectors in terms of environmental impact. Case impact factor data are normalized using a reference statistic, and a weighting is assigned to each key performance indicator to calculate the global score. Individual impact factor values can also be used for benchmarking. Synthetic data are generated through an advanced statistical decomposition algorithm. Advanced data analytics are provided with clustering and a decision tree algorithm using supervised machine learning. Results: Two examples of decision-oriented case studies are used to illustrate how the platform can support the interpretation and use of already computed LCA results in realistic settings. The web-based expert-assisted self-assessment tool, developed in JavaScript, allows users to input their data, benchmark them against project results and perform multidimensional data analysis. The resulting digital tools provide access to LCA data for each use case, generate realistic synthetic datasets preserving key statistical properties, support benchmarking of both project and user-uploaded cases, and perform data analytics, which complement the benchmarking module with a structural and exploratory interpretation of the data. Conclusions: Overall, the tools integrate use case benchmarking, data processing, advanced analytics and user interfaces to facilitate environmental self-assessment and comparison within the BIORADAR framework. Full article

Hepatobiliary surgery is a technically complex subspecialty within general surgery, which requires a comprehensive understanding of complex liver and liver tumour anatomy. The current body of literature highlights the use of three-dimensional-printed liver models (3DPLMs) reconstructed from medical imaging datasets may improve clinician comprehension of patient-specific liver anatomy thus creating a useful tool for hepatobiliary surgical planning and clinician training. The purpose of this systematic review was to examine the clinical utility and feasibility of 3DPLMs in hepatobiliary surgical planning and clinical education and investigate whether these applications influence patient outcomes. Studies were retrieved from three electronic databases (ProQuest, PubMed and Scopus) according to predetermined eligibility criteria. In total, 25 eligible articles were identified, including 18 original research articles and seven case reports. An inductive content analysis approach suitable for heterogeneous bodies of literature was used to synthesise key concepts in this review. There are significant case report and descriptive evidence to support the use of 3DPLMs in clinical education, preoperative planning and intraoperative guidance of patient liver and tumour anatomy to improve hepatobiliary surgical decision making. The studies presented display a large variance in cost and times necessary for the production of 3DPLMs, as studies did not include the software, equipment and full expense of materials used. Additionally, studies concentrated on different aspects of the 3DPLMs production process making them not comparable. This review demonstrates the potential value of 3DPLMs in clinical education, preoperative planning and intraoperative guidance in hepatobiliary anatomy and surgery. Future studies, in particular, randomised controlled trials and experimental research are required to investigate the relationship between 3DPLMs and clinical education and surgical planning outcomes. Full article

This study investigates the application of polymer inclusion membranes (PIMs) for the removal/recovery of 1H-benzotriazole from aqueous solutions, via facilitated transport mechanism, using tri-n-octylamine as a carrier and NaOH as a stripping agent. The process efficiency was analyzed using 1H-benzotriazole flux and permeability through the membrane, its recovery percentage, and the transport process kinetic constant. PIM containing 40% cellulose triacetate, 30% o-nitrophenyl octyl ether and 30% tri-n-octylamine yielded the best results for all four parameters studied due to the role of o-nitrophenyl octyl ether and tri-n-octylamine in reducing the cellulose triacetate polarity, which leads to carrier solubilization on the plasticizer, creating continuous pathways within the membrane and facilitating 1H-benzotriazole transport. Reduced graphene oxide inclusion as the fourth PIM component increases its hydrophobicity, promoting continuous pathway formation and enhancing 1H-benzotriazole transport, which leads to an increase of 10% to 20% in the values of the four parameters analyzed. Ultrasound use in membrane preparation leads to a further increase of 9% to 20% in the values of the four parameters analyzed because the cavitation effect improves the molecular mixing of membrane components and results in a less ordered configuration of cellulose triacetate molecules, thereby reducing their crystallinity degree. All of this significantly improves the interaction between the membrane components and pathway formation, enhancing 1H-benzotriazole transport through the membrane. Full article

The global shift towards miniaturization has positioned micro-manufacturing as a pivotal technology for national industrial advancement, particularly for emerging economies like Malaysia and the broader ASEAN region. This review paper comprehensively examines the concept of micro-manufacturing, delineating its distinction from conventional manufacturing processes and highlighting its inherent benefits. It delves into the transformative potential of micro-manufacturing across key industries, including electronics and semiconductors, medical devices, aerospace and Unmanned Aerial Vehicles (UAVs), automotive, and optoelectronics and photonics. Drawing upon specific examples, national initiatives, and economic implications, this paper illustrates how the strategic adoption and development of micro-manufacturing capabilities can elevate a nation’s technological prowess, foster high-value local industries, enhance export competitiveness, and create a significant multiplying effect across various sectors, thereby contributing to robust and sustainable economic growth. The discussion also incorporates real-world examples from Malaysia, demonstrating the tangible steps taken towards integrating micro-manufacturing into its national development agenda. Full article

Artificial intelligence (AI) is becoming increasingly embedded in the digital infrastructure of local government, creating new opportunities to improve public sector productivity while also influencing systemic risk and organisational resilience across interconnected public systems. As municipalities adopt AI to automate, support, and transform administrative processes, organisational performance becomes more dependent on the reliability of algorithms, the quality of data, effective governance, and coordination among public institutions. These growing interconnections create new vulnerabilities that can spread across public service networks, yet evidence on the productivity, risk, and resilience implications of AI adoption remains fragmented and dispersed across different fields of research. This study develops an integrative conceptual framework that examines the relationship between AI adoption, public sector productivity, systemic risk, and organisational resilience within interconnected sociotechnical systems. Drawing on insights from productivity economics, systems theory, and public governance, the framework positions total factor productivity (TFP) within a broader public value and risk governance perspective. Using the PRISMA 2020 methodology, the study systematically reviews 68 peer reviewed empirical studies published between 2015 and 2025, assessing productivity outcomes, methodological quality, effect sizes, and contextual factors relevant to local government and networked public administration. The findings show that productivity gains associated with AI are strongly influenced by organisational readiness, including digital maturity, workforce capabilities, governance quality, and institutional coordination. While AI has the potential to improve operational efficiency and strengthen adaptive capacity, inadequate readiness can increase systemic risks arising from algorithmic opacity, cybersecurity challenges, data dependence, coordination failures, and disruptions that may spread across interconnected administrative systems. The review also highlights that resilience depends on the ability of public organisations to anticipate, absorb, adapt to, and recover from AI-related disruptions while maintaining the continuity and quality of public services. The study contributes to theory by integrating perspectives from productivity economics, public administration, and systemic risk within a sociotechnical systems framework. It contributes empirically through a comprehensive synthesis of evidence on AI and public sector productivity and methodologically through the application of transparent PRISMA 2020 review procedures. From a practical perspective, the study offers a conceptual measurement framework and policy guidance for municipal decision makers seeking to improve productivity while strengthening resilience and reducing systemic risks in increasingly interconnected public governance systems. Full article

The valorization of agri-food by-products generated during juice extraction represents a key strategy within circular economy frameworks, as it reduces the environmental impact of waste disposal while creating added value and improving the food supply chain. In this work, five betaine-based natural deep eutectic solvents (NaDES) differing in their hydrogen-bond donors, namely citric acid, lactic acid, acetic acid, glycerol, and ethylene glycol, were used for the green extraction of blueberry pomace, a largely underutilized by-product that is nevertheless rich in bioactive compounds. The extracts were characterized by liquid chromatography coupled with diode-array and tandem mass spectrometric detection, allowing targeted profiling of anthocyanins and non-anthocyanin phenolics, including phenolic acids, flavonoids, and phenolic aldehydes. The extraction performance of NaDES was benchmarked against conventional solvents (water and ethanol) to evaluate differences in selectivity and efficiency toward distinct phenolic classes. Antioxidant capacity was determined using DPPH and ABTS radical scavenging assays. Among the NaDES systems, the betaine–citric acid NaDES extract exhibited notable phenolic recovery together with marked radical scavenging activity. After evaluating its inhibitory activity against elastase and tyrosinase, enzymes involved in the skin aging process, the selected NaDES extract was incorporated into a natural-based antiaging cosmetic formulation, and its main physicochemical properties were assessed to verify suitability for topical application. This study demonstrated that the use of NaDES represents an environmentally friendly and sustainable approach to transform blueberry by-products into high-value, safe, and ready-to-use cosmetic functional ingredients without the need for solvent removal. Full article

This research analysed how circular economy practices in the cacao value chain foster socio-economic empowerment and create sustainable employment for Awajún women in Imaza, Amazonas. The overall objective was to determine the association of circular practices with the empowerment and economic benefits of women producers. A quantitative approach was used, employing a non-experimental cross-sectional design and a sample of 55 women, who were administered a structured questionnaire; the data were processed using Spearman’s correlations and multiple linear regression models with robust standard errors. The main results showed a positive and significant correlation between circular economy practices and income and employment generation (rho = 0.702; p < 0.001). Furthermore, the econometric models confirmed that these practices are positively associated with socio-economic empowerment and economic benefits. It is concluded that the circular economy constitutes a viable strategy for improving the living conditions of Awajún women, although its scale up requires overcoming financial, technical and time-related barriers. Full article

Bioeconomy is an important concept of economic development, supported at the highest political levels. However, its successful implementation calls for action within local markets. This study, therefore, examined the market readiness to engage in bioeconomy growth and emerging value chains in Italy, Slovenia, Germany, Poland, Slovakia, and Austria. The objectives were to assess the market readiness for placing novel bioproducts based on by-products and waste from primary production and agri-food processing sectors, and to evaluate the economics of their production. Specific goals were to estimate the availability of by-products and waste used for making new products, evaluate the main directions and trends in the use of by-products and waste, analyse the main barriers and restrictions to by-product and waste supplies to new enterprises and innovative applications, and make an economic assessment of the market entry of innovative products and their development. The study showed that the oil industry, with a high residue potential, was most often chosen to market new products. Other sectors where value chains can be created or modified are the fruit, winery, grain and milling, wood, hemp, and vegetable industries. PESTEL analysis demonstrated that economic factors, at both national and global levels, are the most common barriers to supplying by-products and waste to new business entities. Technological factors also significantly impede the delivery of by-products and waste to such new enterprises and their processing into novel products. In contrast, social conditions are the main factors stimulating supply of by-products and waste to such new plants. The results provide a preliminary insight into the Central European market and its enormous development potential, which is already implicated in the context of growing bioeconomy. Full article

Carbon-neutral ship technologies not only protect the environment but also ensure the maritime sector’s future competitiveness and compliance with international regulations. Therefore, while the transition to carbon-neutral solutions in both port investments and ship technologies is an indispensable part of sustainable maritime transport, some safety risks remain uncertain. This study examines the safety aspects of carbon-neutral ship technologies (hydrogen, ammonia, methanol, battery systems, and other alternative fuels) and demonstrates how risks can be managed within the ALARP (As Low As Reasonably Practicable) framework. For this purpose, a risk matrix was created in the study using probability and severity values, an ALARP classification was made, and FMECA/HAZOP (Failure Mode, Effects, and Criticality Analysis/Hazard and Operability Study) summaries were prepared for critical risks. Subsequently, reasonable and practicable mitigation options were presented for each risk, covering technical, operational, and human factor dimensions. Analyses show that hydrogen poses an explosion risk, ammonia has toxicity and environmental impacts, methanol poses an invisible flame risk, and thermal runaway levels in battery systems are unacceptable. Other fuels (biofuels, LNG derivatives (blue fuels, bio-LNG), synthetic gases, and electro-fuels) offer opportunities in terms of sustainability and infrastructure compatibility but also carry some fundamental risks along with limitations in production capacity. Engineering solutions, operational measures, and human factor practices play a critical role in mitigating all these risks. The widespread adoption of carbon-neutral ship technologies is a process that requires a systematic approach not only to environmental sustainability but also to safety. Full article

Fusarium fungi are known to infect table beet (Beta vulgaris subsp. vulgaris) plants at various stages of development worldwide. Fusarium root rot, which develops post-harvest during long-term storage, is of particular economic significance. In Russia, there is no up-to-date information about the species diversity of pathogens causing this disease of table beets, which determined the purpose of this study. A total of 28 Fusarium isolates were collected from affected beet roots grown in the Moscow region of the Russian Federation from 2018 to 2023 years. Molecular phylogeny based on the TEF-1α and RPB2 genes in combination with morphological characterization showed that five Fusarium species were involved in the pathogenesis of Fusarium root rot of table beet during storage: F. acuminatum (43% of the total number of isolates), F. avenaceum, F. campestre (FTSC); F. sporotrichioides (FSAMSC) and F. solani (FSSC). At the same time, the species F. acuminatum, F. campestre, and F. sporotrichioides were first discovered on beet root in the Russian Federation. Temperature sensitivity of the identified species was studied at 5 °C and 25 °C. According to the value of the cold sensitivity index (CTI) on the nutrient medium and native substrate, the isolates were distributed differently: F. campestre (0.32) > F. acuminatum (0.22) > F. avenaceum (0.21) > F. sporotrichioides (0.19) > F. solani (0.20) and F. acuminatum (0.32) > F. campestre (0.21) > F. solani (0.03) > F. avenaceum and F. sporotrichioides (0.01), respectively. This confirms the need to study the pathogenic properties of isolates on a natural substrate (host plant) under different temperature conditions. When infected with the dominant and most aggressive species F. acuminatum, there was a high variation in the size of the affected area, depending on the genotype of the lines, under both temperature conditions (Va = 2–8 mm³ at 5 °C and Va = 31–1760 mm³ at 25 °C). Therefore, this species can be considered to be the most objective differentiating factor in assessing the resistance of table beet roots to fusarium rot, which determines the need to include it in the breeding process for creating resistant varieties and hybrids for the Central region of Russia. The data obtained in this study are of great importance for developing strategies for managing Fusarium fungi associated with Fusarium rot of beet-root during storage. The research results will also be relevant for other vegetable crops that remain fresh for long periods of time or undergo vernalization in the case of seed production at low temperatures. Full article

In this investigation, optical emission spectrometers, a Brinell hardness tester, optical light and scanning microscopes, and X-ray diffraction were used for general metallurgical characterization of the experimental irons in as-cast states. The hole-drilling method was used to assess residual stress distributions under gross and net casting weight conditions. To create experimental irons using the casting process, raw materials were transformed from a solid to a liquid state using an industrial furnace and ladle to melt and cast, respectively. The casting shakeout temperatures for samples A and B were recorded at 60 °C and 180 °C, respectively, after a characteristic stress lattice casting component was allowed to cool for about 1645 min and 1295 min. Chemical analysis verified the experimental hypoeutectic irons of ASTM A532, Type A, Class III, 25%Cr, i.e., high chromium white cast iron alloys. Additionally, it was discovered that micrographs were made of an austenitic-martensitic matrix that contained eutectic M₇C₃ and secondary M₂₃C₆-type carbides. The residual stress distributions were found to be influenced by various carbide and metallic volume fraction proportions, casting section thickness, and casting shakeout duration and temperature. Optimal hardness values, however, were shown to be associated with higher residual stress distributions and an increase in major alloying elements in experimental irons. Consequently, different residual stress distributions are produced by casting shakeout temperatures at lower and higher values under gross and net casting weight conditions. Full article