Search Results (53,636)

Microbiologically induced calcium carbonate precipitation (MICP) links microbial metabolism with carbonate biomineralization and offers a platform for environmental protection and a circular bioeconomy. This critical review synthesizes ureolytic and non-ureolytic pathways, including denitrification, sulfate reduction, photosynthesis, ammonification and carbonic-anhydrase-mediated routes, and evaluates their efficiency, scalability, environmental impacts and field applicability. MICP can immobilize heavy metals and metalloids, stabilize soils and mine wastes, reduce permeability, control erosion and dust, seal cracks in cementitious materials, and support brine or wastewater treatment. Representative studies report >90% Cd²⁺ removal in selected wastewater systems, 50–90% hydraulic-conductivity reduction at about 10–15% CaCO₃, 2.7 MPa compressive strength in urine-based bio-bricks, 31.87% calcium-source cost reduction using waste-limestone-derived calcium acetate, and geothermal-brine treatment removing 96% Ca, 88% Mn, and 91% Sr while retaining >96% Li. The review emphasizes that circular MICP requires more than waste input substitution; it must include nitrogen management, feedstock quality control, long-term contaminant stability, LCA/TEA, regulatory readiness, biosafety, field monitoring, and technology-readiness assessment. Future research should develop low-ammonia, waste-fed and data-guided MICP systems with standardized quantitative performance metrics. Full article

Alzheimer’s disease (AD) continues to be one of the greatest challenges in public health due to its multifactorial and heterogeneous nature, involving multiple physiological axes that encompass a large number of genetic, metabolic, vascular, and inflammatory interactions. In current clinical practice, medical specialties, mainly neurology and psychiatry, still rely on targeted gene panels for genetic evaluation. Although these panels remain effective for certain predefined hypotheses, their restricted and predefined nature limits the detection of the broader spectrum of genetic variation that may contribute to the complex biological interactions underlying neurodegeneration. Whole-exome sequencing (WES) is, from our clinic-based perspective, one of the most comprehensive genomic approaches currently available, since it allows the analysis of the ~19,500 protein-coding regions, and depending on the library approximately 5500 additional clinically relevant genomic loci, including splice sites, untranslated regions, long non-coding RNAs (lncRNAs), pseudogenes, regulatory elements and mitochondrial DNA (mtDNA). It enables the identification of pathogenic variants and variants of uncertain significance (VUS) under the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification frameworks. It also expands biological interpretation to variants conventionally classified as benign, which, when interpreted collectively, may contribute to pathway-level contextualization within the hypothesis-generating theoretical framework proposed in this review without implying pathogenicity, causal inference, or immediate clinical actionability. Additionally, WES enables the identification of secondary and incidental findings that may provide clinically relevant information beyond the primary phenotype, thereby supporting preventive surveillance and clinical risk management. This review analyzes the use of WES as a strategic platform for personalized decision-making in contemporary practice given the multifactorial and heterogeneous complexity of AD. It also addresses the complexities and limitations of the ACMG/AMP recommendations for filtering and classification of variants, the lack of standardization between reports and platforms, and the need for physician training, which constitute a great challenge for the translation of data to therapeutic decision-making. While the clinical utility of whole-exome sequencing (WES) in genetic diagnosis and precision medicine is well established, this review additionally proposes a hypothesis-generating theoretical framework whereby variants conventionally classified as benign or of uncertain significance may contribute to pathway-level biological contextualization in Alzheimer’s disease. Full article

Gendered leadership theories suggest that women executives may adopt distinct crisis management approaches, yet evidence from private-sector small- and medium-sized enterprises (SMEs) remains limited. This study examines associations between women’s executive presence, crisis strategies, and firm outcomes during COVID-19. Using survey data from 207 SMEs across 12 sectors in Istanbul, Türkiye, we apply non-parametric tests and regression models controlling for firm age, size, and sector. Firms with women executives reported stronger cash-flow sustainability and cost management outcomes but no significant differences in revenue generation or overall performance. They also scored higher on a composite defensive strategy index, although measurable outcome differences were limited to the cost-related dimension. These findings suggest that the association between women’s executive presence and crisis outcomes is domain-specific rather than uniform across performance dimensions. Because the indicator captures executive presence rather than decision-making authority, these associations may also reflect organizational characteristics with which women’s executive presence coincides. Full article

Lean Construction and digital tools such as Building Information Modeling (BIM), common data environments (CDEs), and mobile applications are widely adopted in construction projects but are often implemented through parallel and disconnected workflows. Consequently, Lean production control continues to rely heavily on manual observations, meetings, and spreadsheets, while increasing volumes of digital project data remain underutilized for operational decision-making. This disconnect limits project teams’ ability to detect waste early, stabilize production flow, and learn systematically from recurring issues. This study develops a conceptual Digital Lean Construction (DLC) framework using a design-oriented methodology comprising three stages: synthesis of gaps in existing BIM–Lean integration research, examination of previously validated digital workflows for BIM Quality Control (QC), Quantity Takeoff (QTO), and digital twin monitoring, and integration of these components into a unified closed-loop architecture. The resulting framework organizes project information through four conceptual layers and six implementation components that connect BIM/Industry Foundation Classes (IFC4 × 3) models, schedules, issue and quality records, quantity data, field inputs, sensor information, and GIS-based spatial context. The framework assumes IFC4 × 3 because it provides enhanced support for infrastructure assets and linear referencing required for transportation and civil infrastructure projects. Rule-based analytical logic is formalized for seven Lean key performance indicators (KPIs): Percent Plan Complete (PPC), takt deviations, constraint age, rework cycles, waste event counts, QC status, and delay risk. The framework demonstrates how validated and location-aware project information can be transformed into actionable Lean performance intelligence and incorporated into weekly planning, daily huddles, problem-solving, and standardization routines. Several underlying data-generation components have been validated in previous studies; however, the integrated DLC framework itself remains conceptual and requires project-level empirical evaluation. As a conceptual framework grounded in prior literature and previously validated digital workflows, this study does not include empirical field validation. Instead, it proposes an operational architecture intended to guide future implementation and evaluation in real construction projects. The study contributes an implementable architectural foundation for moving from fragmented, retrospective reporting toward proactive, data-supported, and continuously improving production control. Full article

Mobile networks have become targets of sophisticated cyber attacks. Critical vulnerabilities persist in the General Packet Radio Service Tunneling Protocol (GTP). Signature-based Intrusion Detection Systems (IDS) are inadequate against zero day exploits and novel attack patterns, necessitating more adaptive approaches. We propose GTP-AEGIS (Adaptive Ensemble with Gated Input Selection), a hybrid IDS that integrates signature-based detection with a CatBoost gradient boosting classifier via a Selective Heterogeneous Ensemble (SHE) framework. An Input-Dependent Confidence Gate (IDCG) applies a per-sample priority rule over CatBoost, a NearestCentroid Rule Engine (NCRE), and a signature pathway. A real Suricata engine detects attacks with 100% precision but only 69.2% binary recall when run standalone; within the ensemble, the signature role is played by an idealized Signature-Detection Surrogate (SDS), so the reported ensemble gains are upper bounds. On the evaluated GTP-U dataset, GTP-AEGIS reaches accuracy above 90% with 10% of the training data and raises recall for the rare invalid-TEID class from 48.9% to 64.4%; this improvement comes from the signature pathway rather than the NCRE, and the aggregate accuracy gain is not statistically significant after correction for multiple comparisons. All accuracies are obtained under a packet-level split, which a group-aware comparison shows to be optimistic by approximately 19 percentage points. The model flags 81 to 100% of packets from unseen attack families as non-normal, although this does not constitute unknown-class recognition. We report the limits of signature-only detection and of packet-level evaluation alongside the gains. Full article

Background: Conventional Doppler ultrasound is limited by its angle dependence and its inability to characterize complex flow patterns adequately. Vector flow imaging (VFI) is an angle-independent ultrasound technique that enables two-dimensional velocity vector mapping and the assessment of hemodynamic parameters. This scoping review aims to map the current evidence on the application and validation of VFI for assessing carotid artery stenosis (CAS). Methods: Using the Population–Concept–Context framework, we included studies that evaluated the application, validity, or outcomes of vector flow imaging in individuals with suspected or confirmed carotid artery stenosis, as well as in healthy controls used for comparison or validation, in clinical or research settings. Five electronic databases were searched from inception through 30 April 2026. Studies limited to conventional Doppler ultrasound or to animal or phantom models without human validation were excluded. Data were synthesized using descriptive numerical analysis and narrative thematic synthesis. Results: A total of 48 sources of evidence met the inclusion criteria. Six trial registrations without reported results were excluded from synthesis, leaving 42 synthesized sources, including 40 original studies and two reviews. The most frequently reported parameters were wall shear stress (n = 25), turbulence indices (n = 11), and velocity vectors (n = 14). Most studies were cross-sectional (n = 20) or technical validation studies (n = 13) with small sample sizes (median 31 participants, IQR 10.5–57; range 1–476). The dominant research focus was plaque vulnerability assessment, while fewer studies addressed stenosis grading. Only eight studies reported diagnostic-performance metrics; none employed prespecified thresholds, two reported blinding, and none adhered to the Standards for Reporting Diagnostic Accuracy Studies guidelines (STARD). Conclusions: VFI enables detailed characterization of carotid hemodynamics, but the available evidence remains preliminary and does not establish clinical utility. Standardized, adequately powered studies with external validation are required before clinical implementation. Full article

The transition toward decentralized renewable energy systems creates monitoring problems that current digital infrastructures do not solve: sustainability claims are produced by the same actors they evaluate, environmental evidence is reported periodically rather than observed continuously, and the communities most affected by deployment cannot inspect the data used to represent their territories. Existing integrated platforms combine subsets of the blockchain, Internet of Things (IoT) sensing and life cycle assessment (LCA) at the data layer, but they do not organize that integration through an explicit governance structure. This paper contributes a cybernetic governance framework in which the Viable System Model (VSM) supplies the organizing structure of a blockchain–IoT–LCA monitoring architecture, so that sensing, distributed trust, strategic intelligence and participatory governance are recursively coupled rather than sequentially chained. The framework was developed and evaluated under the Design Science Research paradigm, and instantiated in the IMPACT Energy.CO platform across two technology routes, wind and solar, in La Guajira, Cesar, Atlántico and Magdalena, Colombia. Evaluation against six pre-declared criteria reports 45 executed test cases with a 100% pass rate, 90% unit and 87% integration code coverage, load tests up to 5000 concurrent users with zero errors and sub-second mean response, an operating hash-chained provenance layer issuing verifiable LCA certificates, 14 participatory validation workshops, 199 users trained and 166 technicians certified. We use traceability in a deliberately narrow sense throughout: the property whereby a committed record can be linked to the ingested data series, model version and computation that produced it, and its integrity and ordering checked by a party that does not trust the producer. It is provenance and integrity traceability from the point of ingestion onward, and it is not metrological traceability: the architecture cannot verify that an original sensor measurement corresponds to the physical quantity it purports to represent. We accordingly make explicit what the architecture does not guarantee: a ledger protects records after commitment but cannot certify measurement at the point of capture, and we present a threat model, a set of implemented controls and the residual risk that remains. This study contributes an architecture, a reproducible development and evaluation method, and a calibrated account of what verifiable environmental monitoring can and cannot deliver in contested Global-South territories. Full article

Intrinsically self-sensing cementitious composites offer a promising basis for continuous structural health monitoring. Their electrical response, however, is strongly affected by reversible moisture change and freeze–thaw exposure. This study presents a computational proof-of-concept for the AI-driven design of a federated digital-twin architecture for damage identification and adaptive sensing in sustainable self-sensing cementitious infrastructure. The framework is developed and evaluated entirely in software on a physics-based synthetic testbed. At its present maturity, it is therefore a digital-twin precursor rather than an operational digital twin: it has no calibrated physical counterpart and no live, two-way data coupling, and no experimental validation is claimed. A transparent, physics-based signal generator produces fractional-change-in-resistance signals for twelve virtual CNT/biochar-functionalized LC3 and geopolymer specimens. Each passes through four progressive damage stages interleaved with wet–dry and freeze–thaw conditioning. The framework integrates a CNN-LSTM damage classifier, unsupervised domain adaptation, federated learning, reinforcement-learning-based active sensing, and quantum-inspired aggregation optimization. On three unseen virtual specimens (654 evaluation windows), the CNN-LSTM achieved 70.3% four-stage accuracy (95% Wilson confidence interval 66.7–73.7%) and a macro-F1 score of 0.650, with per-specimen accuracy ranging from 63.8% to 77.1%. It reached 85.2% (95% CI 82.3–87.7%) for the damaged-versus-undamaged decision and reduced environment-induced false alarms by 74.7% (95% CI 61.7–83.4%) relative to a calibrated threshold detector. Federated averaging was less accurate and less stable than centralized training; the 5.2 percentage-point gain from quantum-inspired aggregation lies within the resolution of the evaluation set and is not established as a real improvement. The active-sensing controller reduced measurement cost by 98.9% but detected only four of 27 damage-progression events. All sensing data are synthetic, and every interval reported here is recomputed from the evaluation counts already reported rather than obtained from additional experiments. The results therefore establish algorithmic feasibility only and identify the components requiring refinement before experimental validation. Full article

An atmosphere–ocean–wave-coupled model, the UWIN-CM, running in real-time in the Hong Kong Observatory, has adopted radar data assimilation (DA) and been incorporated with a HAILCAST module in WRF for hail size simulation. This paper analyzes the distribution of maximum hail sizes forecast by the UWIN-CM in comparison with the Maximum Estimated Size of Hail (MESH) from radar for six hail cases reported by human or derived from radar in the Pearl River Estuary of Guangdong Province in 2026. The performance of hail forecast with and without radar DA is compared. The model with DA performed simulates hail at the locations that were consistent with the reported data and/or MESHs in five out of six cases. The timings of simulated hail aligned with reports/MESHs in three cases, and these were delayed by approximately 1 to 3 h in the remaining two. For the average hail diameters, those from simulations were smaller than MESH by around 30 to 50% in two of the five successful cases, while the other three cases had larger diameters than MESH by about 90 to 140%. Without radar DA, hails were simulated in only two out of six cases. The rate of detection was enhanced with radar DA, potentially benefiting from the improved moisture distribution and wind field of the initial conditions. The possible factors behind the differences in hail size between the simulations and MESH are discussed, including the choice of microphysics scheme and the differences in climatology between the PRE, and the contiguous US where the HAILCAST parameters were calibrated. For practical use in operation, parameter tuning of HAILCAST based on the hail climatology of the PRE would be needed. This work paves the way for providing forecasters with early alerts about the occurrence of hail in the region. Full article

Rheumatoid arthritis (RA) is a chronic autoimmune disease in which fatigue and sleep disturbances, in addition to articular symptoms, are of significant importance. These symptoms are among the most common and burdensome complaints reported by patients; they affect their daily functioning and quality of life, and can also exacerbate one another. Currently, the treatment of RA focuses not only on reducing inflammatory activity and preventing structural damage, but also on improving outcomes that matter most to patients. In modern RA treatment, Janus kinase inhibitors (JAKis) are becoming increasingly important; by inhibiting the JAK/STAT pathway, they limit the activity of cytokines involved in the inflammatory response. This review aimed to analyse the effect of selected JAKis on fatigue and sleep quality in patients with RA. An analysis of available study results showed that baricitinib, filgotinib, tofacitinib and upadacitinib reduce fatigue severity. In many cases, improvement was observed as early as the initial stages of treatment and persisted at later follow-up points. At the same time, the extent of this improvement was not uniform and depended on the drug used, the dose, the patient population, and the assessment method adopted. Some analyses also suggested that this effect may have been partly due to reduced pain and improved disease activity. The data on sleep quality are less extensive, but the results suggest that tofacitinib and upadacitinib may also have a beneficial effect in this regard. With tofacitinib, improvements in sleep quality were observed early, affected multiple sleep domains, and, in some studies, persisted over the long term. For upadacitinib, an improvement in sleep quality appeared to be associated with disease control and remission. The smaller number of studies on sleep quality than on fatigue highlights the need to consider this parameter more thoroughly when assessing the efficacy of JAKi treatment and emphasises the importance of a more holistic approach in clinical practice. Full article

Machine learning (ML) provides new opportunities to model the nonlinear relationships among composition, processing, microstructure, defects, properties, and in-service degradation of structural steels. This structured critical review examines ML applications to materials and process design, microstructural characterization, mechanical-property prediction, corrosion, fire and elevated-temperature performance, fatigue, fracture, and remaining-life assessment. Literature published up to 31 July 2026 was searched primarily through the Web of Science Core Collection and Scopus. A total of 110 publications were retained based on their relevance to structural steels, transparency of data and modeling procedures, and availability of information on validation or engineering applicability. The reviewed studies show that model suitability depends strongly on data modality, sample independence, feature representation, and validation strategy rather than on algorithm family alone. ML has progressed from property prediction toward process optimization, inverse materials design, environmental degradation assessment, and fatigue- and crack-related prognostics. However, independent cross-manufacturer, cross-laboratory, production-scale, and field validation remains limited, while uncertainty quantification and applicability-domain assessment are still inconsistently reported. These limitations are particularly important for corrosion, fire, fatigue, and remaining-life applications, where internally validated models should not be interpreted as substitutes for established physical models or design provisions. Future research should prioritize standardized multimodal data, physics-informed and uncertainty-aware modeling, prospective validation, and rigorously evaluated closed-loop monitoring and digital-twin frameworks for structural-steel life-cycle management. Full article

Career decision-making difficulties (CDDs) among female undergraduates are associated with both individual psychological processes and culturally embedded social contexts. This study examined the associations among career anxiety, career decision-making self-efficacy (CDSE), perceived frequency of parental career support, and CDD among female undergraduates from four purposively selected non-elite universities in Jiangsu Province, China. Guided by Social Cognitive Career Theory (SCCT), this explanatory sequential mixed-methods study combined quantitative and qualitative approaches. Quantitative data from 407 participants were analyzed using SPSS 27.0, AMOS 26.0, and PROCESS macro 4.1, including confirmatory factor analysis and conditional process analysis with 5000 bootstrap samples, followed by thematic analysis of semi-structured interviews with 12 participants using NVivo 12. Career anxiety was positively associated with CDD and negatively associated with CDSE, with CDSE partially accounting for the association between anxiety and decision difficulties. The anxiety–CDD association was stronger among students reporting higher frequencies of parental career support behaviors. Qualitative findings suggested that perceived support quality, autonomy support, and contextual fit shaped how parental involvement was experienced. These findings suggest that parental career support should be understood not only in terms of behavioral frequency but also in relation to how involvement is experienced under conditions of heightened career anxiety. Longitudinal, dyadic, and culturally diverse research is needed. Full article

We report early toxicity outcomes after institutional implementation of prostate SBRT using 42.7 Gy in seven fractions delivered with either MR-guided adaptive SBRT (MRgSBRT) or CT-guided non-adaptive SBRT (CTgSBRT). Between July 2019 and May 2023, 216 patients received this regimen. Genitourinary (GU) and gastrointestinal (GI) toxicities were retrospectively assessed using the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Most patients had intermediate-risk disease (86%), and 14% had high-risk disease. Median prostate volume was 40 mL, and median baseline International Prostate Symptom Score (IPSS) was 8 among patients with available data. MRgSBRT and CTgSBRT were used in 100 (46%) and 116 (54%) patients, respectively. At a median follow-up of 19 months, 12- and 24-month grade ≥ 2 GU toxicity rates were 20.0% and 18.2%, while grade ≥ 2 GI toxicity rates were 3.5% and 3.6%, respectively. No statistically significant platform-related differences were detected; however, these comparisons were exploratory and potentially confounded by nonrandomized platform selection, treatment era, rectal-spacer use, adaptive workflow and differing PTV margins. On univariable analysis, baseline GU symptoms were associated with higher 12-month grade ≥ 2 GU toxicity (OR, 3.68; 95% CI, 1.52–10.37; p = 0.007), while prostate-volume category was not significantly associated with this endpoint. Full article

The hotel industry is highly competitive, with hotels seeking new ways to increase market share and boost direct bookings against the dominance of online travel agencies. While previous research has established that hotel website quality influences booking behavior, the role of website aesthetics, specifically dimensions such as photography, design, and text, has remained insufficiently theorized and tested. This paper addresses that gap by proposing and testing a model that is theoretically grounded by integrating the stimulus–organism–response framework, the elaboration likelihood model, and signaling theory to explain how website aesthetic dimensions relate to hotel features and direct booking share. This study employs a content analysis of 201 categorized Croatian hotel websites combined with chi-square analysis and Cramer’s V effect-size estimation. The findings confirm significant associations between hotel features (rating, chain, and consortia membership) and website aesthetic dimensions and between aesthetic dimensions and direct booking share, with photography and text showing the strongest associations within the sample. These results extend our theoretical understanding of website aesthetics as an antecedent of booking behavior and offer hoteliers evidence to prioritize content investment. This study also addresses methodological concerns by reporting effect sizes alongside significance levels and a structured coding protocol. Future research should explore the directionality of these relationships, which is identified as a limitation of this study. This study is deliberately scoped to the aesthetic dimension of hotel websites within the Croatian market; broader website-quality characteristics (e.g., navigation, usability, booking-interface design, page-load speed) and more recent, post-pandemic data are identified as important directions for future research. Full article

Rejuvenation of the perioral region using minimally invasive aesthetic techniques is frequently used to address age-related changes. While hyaluronic acid-based dermal fillers are a frequently used treatment, limited data are available on the injectable biostimulator poly-L-lactic acid (PLLA-SCA; Sculptra^®). This study described the aesthetic outcomes of PLLA-SCA injectable treatment for perioral rejuvenation using a series of patient cases collected up to 8–13 months post-first injection. This retrospective, single-center case series involved adults (age ≥ 18 years) who presented with concerns related to age-associated changes in the perioral region and were treated with PLLA-SCA as part of a full-face rejuvenation regimen. Reconstituted PLLA-SCA was injected subdermally, as superficially as technically feasible, using a 25-gauge blunt-tip cannula equally across both sides of the full face, adjusted to individual findings, at Baseline (Day 0) and at Weeks 8 and 16, with a follow-up at Week 28. This series of patient cases demonstrated positive aesthetic outcomes with PLLA-SCA that included visible softening of the vertical lip lines at rest and restoration of a more horizontal commissural axis, preserved dynamic expression, improved definition of the Cupid’s bow and the vermilion border, reduced prominence of the mentolabial crease, improved midfacial support, and improvement of peri-commissural skin texture. For all cases, the investigator-rated Global Aesthetic Improvement Scale score at Week 28 was either “very much improved” or “much improved”, and the patient-reported satisfaction was rated at 5/5. Adverse events were limited to mild, transient injection-site bruising that quickly resolved without intervention, and short-lived edema; no nodules, vascular events, or delayed-onset reactions were observed. While these preliminary clinical observations at Week 28 suggest that PLLA-SCA can be used in a safe and effective manner for rejuvenation of the perioral region, future, larger, and longer-duration studies are warranted. Full article