Abstract: Moisture damage in buildings has conventionally been discussed mainly in relation to winter condensation in cold climates. In hot-humid buildings, however, deterioration develops under different boundary conditions, including persistently warm and humid outdoor air, frequent rainfall, air-conditioning operation, air leakage, and limited drying after wetting. As climate change increases atmospheric moisture loading and weakens nighttime recovery, these conditions are becoming more consequential not only in established hot-humid regions but also in regions shifting toward more persistently humid climates. This review examines moisture damage in hot-humid buildings as a coupled problem linking climate change, building-envelope moisture response, risk assessment, microbial implications, and building adaptation. Representative scenarios include biological contamination on exterior surfaces, summer condensation and moisture accumulation within envelope assemblies, localized dampness at indoor surfaces and behind furniture, and moisture stagnation in semi-enclosed spaces. These phenomena are interpreted not as isolated defects, but as manifestations of drying deficit. The review discusses climatic drivers, building-physics mechanisms, and major moisture and mold risk indices, including the Fungal Index, VTT Mold Index, IBP-type approaches, MRD, and DR-SIM. It also highlights implications for envelope design, retrofit, ventilation, dehumidification, and operation. Overall, moisture damage in hot-humid buildings is best understood as the outcome of climate-driven drying deficit.

Abstract: The article is devoted to the developing methodological approaches to multi-criteria resource optimization of technological solutions in Nature Use Projects considering the growing shortage of water and energy resources, climate change, and post-war transformation of Ukraine’s agricultural sector. The need to transition from traditional technical and economic optimization models to integrated assessment approaches which consider ecological, resource, and economic aspects of the project implementation effectiveness is substantiated. The methodological basis of the study is a combination of Multi-Criteria Decision-Making and the Water-Energy-Food Nexus concept, enabling the necessary adaptive management and formalizing the process of project decision-making under multifactor uncertainty. A set of indicators of resource-ecological and economic efficiency is proposed, including indicators of productivity, weather and climate risk, resource use, environmental reliability, investment attractiveness, etc. A key feature of this approach is the transformation of resource-ecological indicators into a value form, ensuring their integration with economic indicators within a single optimization model. Based on a machine experiment for the conditions of the Kherson region, an assessment of the effectiveness of various irrigation regimes, which differ from the project irrigation regime in terms of watering and irrigation norms in terms of their level of provision with water and energy resources, was carried out. It was determined that, under the studied conditions, the permissible deficit threshold is approximately 30%, achieving a compromise between economic efficiency and environmental acceptability. Adaptive management of irrigation regimes has been shown to reduce the resource intensity of production without a significant loss of productivity. This creates a basis for revising outdated design standards, which focused on 100% satisfaction of water needs, in favor of adaptive models that account for the real resource potential of the territory. This approach transforms irrigation from a resource-intensive industry into a tool for sustainable territorial development, where the priority is the efficiency of each cubic meter of water and kilowatt-hour of energy used, rather than gross collection. It has been proven that the implementation of resource optimization as a basic principle of natural resource project management contributes to increasing the efficiency of natural capital use, minimizing environmental risks, and ensuring the sustainable development of the agricultural sector. The obtained results can be used to substantiate engineering solutions in projects for the restoration and modernization of water management and land reclamation systems in Ukraine.

Abstract: The sound speed profile (SSP) is a core environmental parameter for underwater acoustic detection, navigation, communication, and other applications. However, its accurate acquisition is constrained by the sparsity of observational data and the ill-posed nature of inversion problems. This paper systematically reviews the research progress of SSP inversion under sparse observation constraints: it combs the technical evolution from physical model-driven methods (Matched Field Processing, MFP; Compressed Sensing, CS) to data-driven approaches (Dictionary Learning, DL; Machine Learning, ML), and classifies and compares the principles, applicable scenarios, advantages, and disadvantages of mainstream methods. It integrates typical measured cases from existing studies (including mesoscale eddy monitoring, underwater navigation and positioning, etc.) and quantitatively analyzes the inversion accuracy and practical value of different technical routes. The research shows that fusing physical constraints with multi-source sparse data (remote sensing, in-situ discrete measurements) is the core direction to balance inversion accuracy, efficiency, and cost. This paper provides a comprehensive reference for technical selection in fields such as marine national defense and resource exploration.

Abstract: 5G‑connected mobile respiratory units introduce a paradigm shift in acute crisis management for lung cancer patients by merging portable ventilatory support with ultra‑low‑latency, high‑bandwidth connectivity. These units integrate on‑board ventilators, non‑invasive and invasive respiratory interfaces, vital‑sign monitors, and 5G modems to enable real‑time transmission of flows, pressures, oxygen saturation, and high‑definition video to remote critical‑care hubs. During transport or in‑field deployment, intensivists and respiratory specialists can guide airway management, titrate ventilator settings, and override parameters via cloud‑based control interfaces, effectively extending ICU‑grade care into ambulances, rural clinics, and home‑based acute episodes. For lung cancer patients experiencing sudden respiratory failure due to tumour‑related airway obstruction, pleural effusion, or post‑procedure complications, such units reduce time‑to‑intervention and improve stabilization before hospital arrival. This article discusses the system architecture, 5G‑enabled tele‑ICU connectivity, safety protocols, and clinical workflows that position 5G‑connected mobile respiratory units as a scalable, technology‑driven solution for managing acute respiratory crises along the lung cancer care continuum.

Abstract: This study focuses on the investigation of the influence of chitosan (CS) and the nature of the support on performance of the hybrid catalysts (Pd-CS/support) in low-temperature hydrogenation of allyl alcohol (2-propen-1-ol). CS-containing palladium catalysts were prepared via sequential deposition of the polysaccharide and palladium onto metal oxide supports (commercial MgO, SiO₂, TiO₂ and synthesized alumina). The synthesized CS-modified palladium catalysts were compared with their polymer-free counterparts. The successful formation of catalysts was confirmed using TGA, XPS, HAADF-STEM, and viscosimetric analysis. The results of low-temperature hydrogenation of 2-propen-1-ol indicate that catalytic activity and selectivity are influenced by both the support nature and chitosan modification. Overall, the introduction of chitosan had a positive effect on both the structural (Pd nanoparticle dispersion and convergence of the electronic properties of the catalysts) and catalytic (activity and selectivity) properties. The obtained results may contribute to controlling reaction pathways in the desired direction in the selective valorization of platform molecules.

Abstract: The increasing reliance on digital infrastructures has made electronic records management systems (ERMS) essential for ensuring organisational governance, accountability, and effective service delivery. This study presents a structured qualitative literature review of ERMS implementation across developed and developing contexts, with the aim of identifying key determinants, recurring challenges, and contextual variations in adoption patterns. Drawing on studies published between 2010 and 2024, the review adopts a socio-technical analytical framework that categorises ERMS implementation determinants into organisational, technological, and environmental dimensions. The findings reveal that successful implementation depends on the alignment of governance and policy frameworks (environmental), technological infrastructure and system capabilities (technological), and human resource capacity and organisational culture (organisational). The analysis further demonstrates that these determinants are highly interdependent and vary across contexts. In developing environments, implementation is primarily constrained by infrastructural limitations, financial constraints, and shortages of technical expertise. In contrast, in more digitally mature contexts, challenges shift toward system interoperability, usability, and metadata standardisation. This study contributes to the literature by providing an integrated analytical framework that synthesises fragmented empirical findings and advances a more structured understanding of ERMS implementation as a sociotechnical process. The findings offer practical implications for policymakers and institutions seeking to strengthen digital records management and information governance. Future research should prioritise longitudinal and cross-national studies to further advance theoretical development in this field.

Abstract: Phosphodiesterase-1 (PDE1) represents an attractive target for the treatment of idiopathic pulmonary fibrosis (IPF). However, the limited chemical diversity of current PDE1 inhibitors has hindered the development of potential anti-IPF drugs, primarily due to an ambiguous understanding of interactions between inhibitors and PDE1. Herein, we report an integrated virtual screening strategy containing pharmacophore modeling, molecular docking, and molecular dynamics simulations, which markedly accelerated the discovery of novel PDE1 inhibitors. Enzymatic assays identified eleven active compounds with moderate inhibition from twenty-six purchased candidates, encompassing nine distinct scaffold types. Notably, 6484-0008 and 6484-0032 exhibited more than 50% inhibition at a concentration of 1 μM. Hydrogen bonding analysis and residue-based energy decompositions revealed key recognition mechanisms involving crucial residues Gln421, His373, and Phe424, as well as the unique Thr271 in the flexible H-loop region, providing insights for the rational design of inhibitors with enhanced potency.

Abstract: While deep learning systems are becoming increasingly prevalent in medical image analysis, their vulnerabilities to adversarial perturbations raise serious concerns for clinical deployment. These vulnerability evaluations largely rely on Attack Success Rate (ASR), a binary metric that indicates solely whether an attack is successful. However, the ASR metric does not account for other factors, such as perturbation strength, perceptual image quality, and cross-architecture attack transferability, and therefore, the interpretation is incomplete. This gap requires consideration, as complex, large-scale deep learning systems, including Vision Transformers (ViTs), are increasingly challenging the dominance of Convolutional Neural Networks (CNNs). These architectures learn differently, and it is unclear whether a single metric, e.g., ASR, can effectively capture adversarial behavior. To address this, we perform a systematic empirical study on four medical image datasets: PathMNIST, DermaMNIST, RetinaMNIST, and CheXpert. We evaluate seven models (VGG-16, ResNet-50, DenseNet-121, Inception-v3, DeiT, Swin Transformer, and ViT-B/16) against seven attack methods at five perturbation budgets, measuring ASR, Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and $L_2$ perturbation magnitude. Our findings show a consistent pattern: perceptual and distortion metrics are strongly associated with one another and exhibit minimal correlation with ASR. This applies to both CNNs and ViTs. The results demonstrate that ASR alone is an inadequate indicator of adversarial robustness and transferability. Consequently, we argue that a thorough assessment of adversarial risk in medical AI necessitates multi-metric frameworks that encompass not only the attack efficacy but also its methodology and associated overheads.

Abstract: Background/Objectives: Respiratory syncytial virus (RSV) is a major cause of respiratory illness across the lifespan, yet its health-economic burden in adults remains underrecognized. Building on a previously published nationwide analysis of RSV-associated hospitalizations in Switzerland (2017–2023), this study aimed to estimate age-specific direct inpatient hospitalization costs and assess their implications for healthcare systems. Methods: We conducted a nationwide health-economic analysis using Swiss Federal Statistical Office (FSO) hospitalization data (2017–2023) combined with SwissDRG-based cost statistics (2024). Age-specific costs per hospitalization were applied to RSV-associated hospitalization counts. To account for disease severity, additional estimates were derived using RSV-specific length-of-stay (LOS) ratios compared with all-cause hospitalizations. Results: Total RSV-associated hospitalization costs were estimated at CHF 55.1–70.2 million annually. Children aged 0–9 years accounted for the highest number of hospitalizations and the largest share of total costs (CHF 27.8–34.3 million). Despite fewer hospitalizations, adults aged ≥60 years generated comparable total costs (CHF 23.6–31.1 million), driven by substantially higher costs per case. Costs increased markedly with age, reflecting longer hospital stays and higher clinical severity. Conclusions: RSV-associated hospitalizations impose a substantial economic burden on the Swiss healthcare system. The disproportionate contribution of older adults highlights the importance of targeted prevention strategies and provides a foundation for future health-economic evaluations and policy decision-making. Respiratory syncytial virus (RSV) is a major cause of respiratory illness across the lifespan, yet its health-economic burden in adults, particularly older adults, remains underrecognized. Building on a previously published nationwide analysis of RSV-associated hospitalizations in Switzerland (2017–2023), we estimated age-specific direct inpatient hospitalization costs by combining national hospitalization data with SwissDRG-based cost statistics from the Swiss Federal Office of Public Health (2024) and length-of-stay–based adjustments to reflect disease severity. Overall, RSV-associated hospitalization costs were estimated at approximately CHF 55.1–70.2 million per year across all age groups. Children aged 0–9 years accounted for the highest number of hospitalizations and the largest share of total costs (CHF 27.8–34.3 million annually). Despite substantially fewer hospitalizations, adults aged ≥60 years generated comparable costs (CHF 23.6–31.1 million), driven by markedly higher costs per case. Average costs per hospitalization ranged from CHF 8,100–10,000 in children and CHF 17,000–22,800 in older adults. Costs increased steeply with age, with more than a 45-fold difference between adults aged ≥80 years and those aged 20–29 years. These findings demonstrate that RSV-associated hospitalizations impose a substantial health-economic burden in young and older age and highlight the disproportionate contribution of older adults to inpatient costs, reinforcing the importance of targeted RSV prevention strategies in high-risk and ageing populations.

Abstract: Remote sensing has become a core technology for environmental and climate monitoring, supported by expanding sensor constellations, advanced processing capabilities, and coordination frameworks established by the European Space Agency (ESA), Global Earth Observation System of Systems (GEOSS), and Committee on Earth Observation Satellites (CEOS). Ensuring consistency across missions requires robust geometric and radiometric calibration and validation. However, traditional reliance on ground control points (GCPs) is limited by sparse global coverage, temporal instability, and dependence on surveyed accuracy. While alternative geospatial datasets, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) point clouds, and vector databases, can serve as references, challenges remain in data access, automation, and cross-sensor applicability. This study proposes a generative adversarial network (GAN)–based approach to generate geometrically consistent image chips from vector maps. Two models were trained at 50 cm and 10 m resolution within the ESA-supported Generative Ground Control Point (GenCP) study, using Sentinel-2 and very-high-resolution RGB imagery. The generated GenCP image chips are evaluated using image-based similarity (radiometric consistency), geometric, and model-performance metrics. Results demonstrate their suitability for automated Cal/Val workflows and their potential as scalable, fit-for-purpose reference datasets.

Abstract: Regulation of the cell cycle is critical for maintaining genomic integrity. Therefore, cells have adapted several mechanisms to ensure that cell cycle events occur in a precise order. Some mechanisms regulate cell cycle progression by inhibiting cell cycle drivers, cyclin dependent kinases (CDKs). The Wee1/Myt1 family of kinases regulate the G2 to M phase transition by phosphorylating and inactivating Cdk1. Investigations of Wee1/Myt1 have mainly focused on its regulation of mitosis; the role of Wee1/Myt1 kinases in the meiotic cell cycle is less well understood. However, misregulation of Wee1/Myt1 during meiosis can have a range of fertility consequences from mild to severe, including human fertilization failure and infertility. Studies from several organisms reveals that the meiotic functions of Wee1/Myt1 kinases differ from mitosis depending on the species and sex. Here, we review how Wee1/Myt1 kinases regulate cell-cycle progression in meiosis across species. We highlight current knowledge of Wee1/Myt1 in meiosis and discuss unanswered questions and new directions to advance the fields of meiosis, reproduction, and development. Understanding the molecular and cellular functions of Wee1/Myt1 homologs in these various systems may contribute to the discovery of the mechanisms underlying human infertility cases, better diagnoses, and clinical treatments.

Abstract: IIce hockey represents a sport with predominantly anaerobic efforts best reflected by repeated sprint ability (RSA) testing (5x5 seconds with 10 seconds recovery). A controversy persists about the usefulness of V̇O2 max laboratory testing for the assessment of ice hockey players. The purpose of the study was to evaluate the relationship between laboratory measured V̇O2 max and RSA simulated on a supine ergometer and tested on ice. Elite male hockey players (n = 64) were tested in the laboratory (V̇O2 max and RSA). RSA was performed by modified Wingate test (5 x 5-seconds sprints with 10 seconds recovery). In 28 athletes RSA were assessed during an on-ice testing (5 maximal skating sprints between the goal and the blue line). The decrease in performance was assessed by fatigue indices. In the laboratory settings the V̇O2 max correlated significantly with maximum workloads of the 2nd, 3rd, 4th and 5th bout with increasing correlation strength (r= 0.26, p=0.02; r=0.48, p< 0.001; r=0.57, p< 0.001; and r=0.60, p< 0.001) and with fatigue indices - % workload decrement index (r = 0.44, p< 0.001) and % maximum average workload decrement (%) (r=0.38, p=0.002). In addition, V̇O2 max correlated with lactate levels after 10 minutes of recovery (r=0.31, p=0.01). There was no correlation between V̇O2 max and on-ice testing results. Moreover, the results of RSA measured in laboratory and on ice did not show any correlation. The lack of relationship between laboratory and on-ice testing is further challenging the usefulness of bicycle ergometry laboratory testing in ice hockey.

Abstract: Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by the simultaneous disruption of interconnected molecular pathways, yet the structural mechanisms underlying this transcriptional disintegration remain poorly characterized. To address this, we constructed condition-specific gene co-expression networks from DLPFC bulk RNA-seq data, using a mutual information framework with Infomap community partitioning. Functional enrichment of network communities via Ingenuity Pathway Analysis (IPA) identified GABAergic signaling, SNARE complex assembly, Synaptogenesis, and Neurexins and Neuroligins interactions as significantly overrepresented pathways. Integration of node degree with condition-specific average expression revealed coordinated topological centralization of key synaptic genes — including NRXN2, LRRTM1, DLGAP3, and SHANK1 — alongside a widespread transcriptional downregulation in GABAergic and Synaptogenesis modules. Shortest path analysis further demonstrated a consistent expansion of intra-pathway distances across all evaluated canonical pathways in AD, quantifying a progressive loss of local communication efficiency. These findings reframe LOAD as an active structural rewiring process, in which the transcriptional network consolidates remaining resources around essential synaptic components as a molecular signature of the pathological state.

Abstract: This report describes the practical implementation of a maximum power point tracking (MPPT) system for a string of four series‑connected monocrystalline silicon photovoltaic (PV) cells. The system includes a boost DC‑DC converter that interfaces the low‑voltage PV string to a 36 V battery, and each cell has an individual MOSFET bypass switch to mitigate partial shading. We explain the operating principles, the MPPT algorithms (Perturb & Observe and Incremental Conductance), the bypass logic, and the closed‑loop control that adjusts the converter’s duty cycle to maximise power transfer. Step‑by‑step descriptions and supporting figures clarify the process.

Abstract: Laser polishing (LP) is widely employed to enhance the surface quality of additively manufactured (AM) metals; however, its behaviour within deep or confined internal geometries remains insufficiently understood. Many high-performance AM components, such as biomedical implants, turbine cooling channels, and metal microfluidic systems, incorporate narrow internal features where heat-transfer conditions differ significantly from open surfaces. In this study, laser powder bed fusion (LPBF)-fabricated 316L stainless steel specimens containing ~10 mm deep slots with widths ranging from 1 to 5 mm were subjected to laser polishing using a continuous-wave fibre laser (power: 80–120 W, scan speed: 450–750 mm/s, spot size: ~80–100 µm, ~60–70% track overlap, single-pass strategy). The influence of internal geometric confinement on microstructural evolution and mechanical response was systematically investigated. A pronounced depth-dependent microhardness gradient was observed along the slot wall, with hardness decreasing from approximately 270 HV in the lower region to ~210 HV near the slot opening, with more significant gradients in narrower geometries. Quantitative grain-size analysis revealed finer grains (~8–12 µm) in the lower region and coarser grains (~18–25 µm) toward the upper region, indicating progressive grain coarsening with increasing height. These variations are attributed to geometry-dependent thermal boundary conditions, where enhanced conductive coupling to the bulk substrate in the lower region promotes higher cooling rates, while reduced thermal extraction near the slot opening results in slower solidification. The results provide clear experimental evidence that internal geometric confinement can significantly influence microstructure–property evolution during laser polishing, even under constant processing parameters. This study highlights the importance of incorporating geometric effects into post-processing strategies for AM components and offers practical insights for achieving more predictable and uniform mechanical performance in confined internal features.

Abstract: N-Methyl-D-aspartate (NMDA) receptors are ligand- and voltage-gated ion channels essential for synaptic plasticity, learning, and memory. The GluN2B subunit, highly expressed in the forebrain and spinal cord, is implicated in multiple neurological and psychiatric disorders, making it an attractive target for positron emission tomography (PET) imaging. However, the development of selective GluN2B PET radioligands remains challenging. Here, we describe the design, synthesis, and evaluation of eighteen 3-alkylaryl derivatives of 7-methoxy-2,3,4,5-tetrahydro-1H-benzo[d]azepin-1-ol, including enantiomerically resolved compounds, as candidate PET radioligands. Structure–activity relationship studies show that binding affinity is largely insensitive to electronic and steric variation at the terminal aryl group but strongly dependent on alkyl linker length, with a four-carbon chain providing optimal affinity. Binding affinity does not correlate with calculated lipophilicity, suggesting hydrophobicity is not the primary determinant of receptor interaction. Absolute configuration was established using vibrational circular dichroism and infrared spectroscopy, and docking studies provided insight into enantiomer-specific binding modes. Two ligands, L3 and L6, and their enantiomers exhibited high GluN2B affinity, favorable physicochemical properties, and suitability for carbon-11 labeling. PET imaging confirmed strong and specific brain binding of the radiolabeled compounds. These findings establish this scaffold as a promising platform for GluN2B PET ligand development.

Abstract: This study examines the microspherical high-calcium fly ash (HCFA) and the high-strength binder material based on it by method of scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS). The composition of 568 individual microspheres of the initial HCFA was determined and presented as ternary diagrams CaO–Al2O3–SiO2 and CaO–FeO–SiO2. The binder specimens have a compressive strength of 24–90 MPa at a curing time of 3–300 days. Their strength is close to that of CEM I 42.5N cement specimens with a curing time of up to 28 days, but exceeds it with a curing time of up to 300 days. The SEM-EDS method showed that the predominant composition of hydration products is concentrated in the high-calcium region of the CaO–Al2O3–SiO2 diagram with a CaO content of 60–80%. The SiO2 content in them is 15-30%, and their composition includes 1–15% Al2O3 and 5–14% FeO. The SEM-EDS method allowed us to understand the transformation of calcium silicate glass microspheres into C-S-H gel, which is the main component of the strengthening matrix. The results contribute to the data for development of models for predicting the effect of HCFA on the properties of composite binders.

Abstract: This review aims to provide comprehensive and practical information on the once-nearly-forgotten but now resurgent roles and trends of autologous transplantation in leukemias. We seek to categorize when it is necessary as a first-line treatment (plasma cell leukemia) and to identify well-defined patient subgroups (such as certain types with intermediate prognosis in AML, APL second remission, etc.) in which autologous transplantation might be comparably or even slightly more effective than allogeneic transplantation, not only in frail patients. In some leukemias, such as CLL, autologous transplantation still does not play a role. Attempts to achieve anti-leukaemic effects in autologous settings have proven largely ineffective, but new approaches might be promising. Newer cell therapies (such as CAR-T) are significantly more effective, and the same applies to in vitro graft purging. However, this area has been investigated relatively recently in an innovative manner, using specific graft pretreatments that may also stimulate anti-leukemic immune responses in autologous cases.

Abstract: This study presents the first comprehensive molecular characterization of Escherichia coli producing extended-spectrum beta-lactamases (ESBL-Ec) in surface waters in Albania, focusing on the Shkumbini river. Antimicrobial resistance (AMR) in aquatic ecosystems poses a significant threat to public health, yet data from Albania remain scarce. Thirty water samples were collected from six locations near Elbasan between September 2022 and February 2024. Following the WHO Tricycle protocol, 52 ESBL-Ec isolates were recovered and characterized for antimicrobial susceptibility, biofilm formation, resistance genotypes and clonal relatedness via pulsed-field gel electrophoresis (PFGE). ESBL-Ec was detected in 80% of the samples analyzed, with 94.2% of the isolates classified as multidrug-resistant (MDR). High resistance frequencies were observed for ampicillin (98.1%) and cefotaxime (86.5%), while 7.7% of the isolates displayed colistin resistance associated with the mcr-3 gene. The bla_CTX-M-1 genotype was the most prevalent (57.7%), and almost half of the isolates harbored multiple ESBL genes. Phylogroup A (46.2%) predominated, followed by the high-risk extraintestinal lineages B2 (23.1%) and D (11.5%). PFGE revealed high genetic heterogeneity, with 51 distinct pulsotypes indicating multiple sources of contamination, such as untreated municipal, agricultural and industrial waste. Additionally, 55.8% of the isolates were capable of forming biofilms. These results highlight the critical role of the Shkumbini river as a reservoir for highly resistant pathogens and emphasize the urgent need for integrated environmental surveillance and improved wastewater management in Albania.

Abstract: Construction and demolition waste (CDW) is the largest single waste stream in the European Union by weight (~39% of all EU waste), yet the EU’s circular material use rate stood at only 12.2% in 2024 — less than half its 2030 target. Despite two decades of legislative ambition, the 70% recovery target under Directive 2008/98/EC has not been genuinely achieved: apparent compliance by most Member States conceals widespread downcycling and inconsistent reporting. This review identifies five persistent barrier domains — legal, technical, social, behavioural, and economic — with regulatory fragmentation and secondary material devaluation as the most structurally entrenched. A decisive paradigm shift is observed in recent research, from material characterisation towards systemic circularity, digital demolition frameworks, and governance. Emerging technologies — including AI-powered sorting, Building Information Modelling, Digital Twins, and Digital Product Passports — hold transformative potential, while Design for Deconstruction represents a critical upstream strategy the sector has yet to mainstream. The forthcoming EU Circular Economy Act will introduce legally binding obligations for Member States. The 2026 Strait of Hormuz energy crisis has reframed CDW from an environmental concern into a strategic industrial imperative: as virgin material costs surge, secondary CDW materials offer economic and geopolitical advantage. Future research must prioritise collaborative governance, longitudinal data, and scalable digital solutions.