Search Results (19,568)

Background/Objectives: Clinical alarm management in continuous patient monitoring systems remains a major challenge in intensive care units (ICUs). The high frequency of nonactionable alarms contributes to alarm fatigue among healthcare professionals, potentially compromising patient safety, clinical surveillance, and the quality of nursing care. As nurses play a central role in monitoring critically ill patients, evidence-based alarm management strategies are essential to improve the quality of care and patient outcomes. This review aimed to synthesize the scientific evidence on nursing interventions for managing clinical alarms in continuous monitoring systems and their contribution to patient safety and quality of care among critically ill patients. Methods: An integrative literature review was conducted following the methodological framework proposed by Whittemore and Knafl. A comprehensive literature search was performed in CINAHL Plus with Full Text, MEDLINE with Full Text, Supplemental Index, Complementary Index, Academic Search Index, the Directory of Open Access Journals (via EBSCOhost^®), PubMed, Scopus, and ScienceDirect. Studies published between 2020 and 2025 in English, Portuguese, or Spanish were eligible for inclusion. Methodological quality was assessed using the Joanna Briggs Institute critical appraisal tools. Nine studies met the eligibility criteria and were included in the final synthesis. Results: The identified interventions were grouped into five main domains: alarm parameter customization, nurse education and training, implementation of structured protocols and alarm management bundles, optimization of monitoring devices and sensors, and interventions addressing human and organizational factors. The evidence indicated that multifaceted and integrated interventions were associated with reductions in nonactionable alarms and improvements in clinical responses to alarms. However, their effectiveness in reducing alarm fatigue appeared to depend on organizational culture, staff engagement, and contextual factors. Conclusions: Effective alarm management requires the consistent implementation of evidence-based nursing interventions. Nurses play a pivotal role in promoting patient safety through clinical expertise, technological competence, and adherence to structured alarm management practices. Strengthening alarm management strategies may contribute to improved quality of care, safer care delivery, and better outcomes for critically ill patients. Full article

Despite a growing range of effective monotherapies for childhood myopia control, a subset of children continues to show suboptimal control, prompting interest in combination therapy. This narrative mini-review summarises recent evidence on combining pharmacological, optical, and device-based treatments to slow myopia progression, with emphasis on axial length (AL) as the benchmark of efficacy. The most studied combination is low-dose atropine plus orthokeratology (OK), with multiple studies and meta-analyses reporting greater slowing of AL elongation than OK alone, particularly in younger children and faster progressors. Emerging evidence supports combining low-dose atropine with other refractive interventions, such as defocus-incorporated multisegment (DIMS) and highly aspherical lenslets (HALs), and dual-focus soft contact lenses, although findings vary by study design, atropine dose, and cohort characteristics. Repeated low-level red light (RLRL) therapy combined with OK or DIMS spectacles has also shown improved AL outcomes in some studies, but retinal safety signals and rebound after cessation require careful monitoring. Combination therapy may be most appropriate for fast progressors, notably those with greater than 0.2 mm over 12 months or for inadequate responders to monotherapy, with stepwise escalation guided by AL response, safety, and adherence. Further long-term, randomised trials with standardised endpoints and responder definitions are needed. Full article

The benefits of lenalidomide, which leverages TP53-dependent apoptosis and promotion of megakaryocytic differentiation, in lower-risk MDS (LR-MDS) with del(5q) are well-established and drive its frequent use in clinical practice. In parallel, advances in molecular testing have elucidated the clear impact of TP53 mutations on response to therapies and prognosis, with diversity in the latter informed by variant allele frequency (VAF) and/or predicted allelic state. In this review, we discuss the converging pre-clinical and clinical evidence that implicates TP53 mutations not only as a driver of lenalidomide resistance in del(5q) LR-MDS, but as a source of selective clonal advantage under lenalidomide exposure. Lenalidomide-induced CK1α degradation triggers TP53-mediated apoptosis in wild-type clones, inadvertently favoring the survival and expansion of TP53-mutated cells. Clinically, this dynamic has been demonstrated across multiple studies, with rising TP53 variant allele frequency and clonal evolution observed following treatment. These findings underscore the importance of baseline molecular assessment in patients with MDS and, in select cases, serial monitoring during therapy. Investigational approaches for del(5q) LR-MDS with the TP53 mutation include GATA2-directed strategies aimed at restoring lenalidomide sensitivity, as well as immune-based therapies targeting the tumor microenvironment characteristic of TP53-mutated disease. Full article

Background/Objectives: Congenital chylous ascites is a rare neonatal condition characterized by the accumulation of lymphatic fluid within the peritoneal cavity. The disorder can be difficult to manage, as many infants show limited response to standard conservative strategies such as dietary modification and supportive care. Currently, no universally accepted therapeutic guidelines exist. We report the successful use of propranolol in the management of refractory congenital chylous ascites. Methods: Clinical data were collected from a 35-week preterm male infant who had prenatal ultrasound evidence of fetal ascites from the 28th week of gestation. Postnatal management initially included fasting, total parenteral nutrition, and from day 9 of life, continuous infusion of octreotide. Due to the persistent ascites, oral propranolol was added to the therapy on the 31st day of life. Current literature was reviewed to compare our findings with those available. Results: Following the addition of propranolol to ongoing octreotide therapy, the infant demonstrated gradual clinical improvement with decreased abdominal distension and reduction of ascitic fluid; as propranolol and octreotide were administered concurrently for approximately 30 days, a causal effect could not be isolated to propranolol alone. Oral propranolol was administered at 0.5 mg/kg every 6 h (2 mg/kg/day total), with heart rate, blood pressure, and glucose monitored throughout treatment; no propranolol-related adverse events (bradycardia, hypotension, bronchospasm, hypoglycemia, or feeding intolerance) occurred. Ultrasonographic resolution of ascites was achieved by day 48, the peritoneal drainage catheter having already been removed on day 34; propranolol was subsequently tapered and discontinued by day 68, and the patient was discharged in stable condition on day 93, with no recurrence on serial ultrasound over the 45 days from resolution to discharge. A narrative review of the literature identified nine infants with lymphatic disorders successfully treated with propranolol. Conclusions: This case suggests a possible temporal association between propranolol administration and clinical improvement in a neonate with congenital chylous ascites refractory to conventional management; no propranolol-related adverse events were observed during treatment. Given the rarity of this condition and the absence of standardized treatment guidelines, further studies—potentially through multicenter registries or prospective case series—are warranted to establish optimal dosing strategies, evaluate long-term outcomes, and clarify the role of propranolol in this setting. Full article

This study presents a multi-methodological approach combining subsurface characterization with dynamic structural assessment to evaluate Soil–Structure Interaction (SSI) mechanisms at the Palazzo Centrale. The 3D Electrical Resistivity Tomography (ERT) and active Multichannel Analysis of Surface Waves (MASW) results were compared with a lithostratigraphic core log to outline the subsurface framework. The stratigraphic framework mapped geotechnical heterogeneities within the upper 6.0 m, where a low-resistivity anomaly (≤1 log(Ω·m)) outlines a mechanically weakened, water-saturated cover deposit overlaying the basaltic lava. This characterization provides the physical baseline useful for interpreting the site response. In this framework, the ambient vibration recordings performed at the free-field sites exhibit a flat Horizontal-to-Vertical Spectral Ratio (HVSR) response within the 1.0–10.0 Hz range, whereas a localized stratigraphic peak emerges at higher frequencies near 15.0 Hz, particularly evident in the building’s courtyard. The building resonance frequency peaks, derived from the Horizontal-to-Horizontal Spectral Ratio (HHSR) analysis at 3.74 ± 0.09 Hz (NS) and 3.58 ± 0.22 Hz (EW), do not overlap with the site resonance frequencies, demonstrating a dynamic decoupling between the soil and the building within the low-to-medium frequency domain. Conversely, the secondary stratigraphic peak near 15.0 Hz overlaps with higher-order structural frequencies tracked in the HHSR datasets. Given the localized nature of this stratigraphic peak and the involvement of higher-order structural modes, this overlap suggests a limited, localized high-frequency amplification confined to specific architectural components, rather than a global site-structure hazard. Furthermore, torsional analysis reveals significant effects within the 3.8–4.0 Hz frequency band, targeting the North-East corner (peak value of 2.85 at station A4), indicating a localized dynamic anomaly due to structural heterogeneities. Overall, this multi-method approach proves highly effective for non-invasive structural diagnostics, establishing a rigorous physical reference that could be successfully integrated into future preventive conservation frameworks and routine monitoring protocols for ancient architectural heritage. Full article

Winter-sport wearable technology spans motion and force sensing, physiological monitoring, thermal intervention, flexible bioelectronics, equipment-integrated systems, and safety technologies. This structured critical review synthesizes an evidence base of 80 unique scholarly records identified through a systematic Boolean search executed on 15 August 2026 in four standard academic databases (Scopus, Web of Science Core Collection, PubMed, and IEEE Xplore), which retrieved 1466 records (808 unique after cross-database deduplication), supplemented by backward/forward citation chasing for eligible records not indexed in these databases. The corpus comprises 32 direct winter-sport records, 15 cold-context translational records, 14 contextual validation records, and 19 secondary/background records. For empirical records containing sufficient information, validation maturity was additionally coded on a seven-stage ordinal scale; 54/80 records could be staged without inference, whereas 26/80 were retained as ‘not staged’. The corpus shows that translational maturity is strongly domain dependent. Motion and kinematic sensing frequently reaches real winter-sport training or field settings, whereas antifreezing hydrogels and flexible bioelectronics have advanced substantially in conductivity, adhesion, self-healing, conformability, and low-temperature operation but remain concentrated at material, integrated-device, and human-demonstration stages. The five recurring constraints—thermodynamic, interface, ecological, connectivity, and equity—are therefore reframed as non-equivalent, context-dependent dimensions rather than universal burdens. The revised architecture also distinguishes digitally mediated sense–decide–actuate loops from material-native stimulus–response and hybrid pathways, while continuous remote monitoring is treated as one option within an energy–communication trade-space. The resulting framework links evidence type, validation depth, system interface, and deployment context without equating commercial availability with scientific validation. Full article

Tetrapod piled jacket foundations, widely adopted for large-capacity offshore wind turbines, are frequently affected by scour, which substantially alters their lateral mechanical responses. Nevertheless, existing studies on this subject remain limited and mostly adopt simplified uniform scour assumptions that deviate significantly from actual field conditions. This study conducted lateral-loading model tests on scoured tetrapod piled jacket foundations, with the local scour geometry idealized based on the non-uniform scour-hole morphology reported in field monitoring and flume test studies. The evolution law of the lateral bearing capacity of the foundations with scour development is revealed, and the differences in lateral bearing performance under uniform and non-uniform scour are systematically compared. A three-dimensional finite element model is established and validated against test data to verify its accuracy and reliability. Additionally, comprehensive parametric analyses are performed to supplement the experimental results, exploring the influences of flow angles, corresponding scour-hole morphologies and lateral load directions on the lateral bearing performance of tetrapod piled jacket foundations. The pile bearing mechanism and internal force distribution characteristics are further clarified. The research findings can provide a theoretical basis for the safe service of offshore wind turbines supported by tetrapod piled jacket foundations. Full article

Anisotropy is a first-order control on rock mass behaviour in foliated, veined, and fabric-controlled ground, yet it remains underrepresented in routine geotechnical practice. This paper presents a review of the literature on anisotropic rock mass behaviour, organised around three identified gaps: the absence of an integrated explanation linking structure, and excavation response; the underdeveloped treatment of spatially variable anisotropy in mine-scale numerical models; and the limited incorporation of precursory monitoring evidence into mainstream geomechanical design. The review is selective rather than encyclopaedic, covering experimental characterisation of directional strength and stiffness, the mechanical role of microstructure and fabric morphology, excavation damaged zone development, constitutive and spatial modelling strategies, seismic source characterisation, laboratory precursor detection, and data collection practice. The review finds that anisotropy changes the path to failure and the spatial organisation of damage, not merely the peak strength, and that constitutive sophistication without a geologically admissible representation of fabric is insufficient to reproduce the mechanism, location, and temporal evolution of damage around underground excavations. Full article

Urban Internet-of-Things (IoT) infrastructures increasingly host distributed artificial intelligence workloads across heterogeneous edge environments, supporting applications such as urban monitoring, resource optimization, and large-scale sensing analytics. Despite the rapid adoption of edge AI, current systems lack a unified architectural layer responsible for orchestrating distributed intelligence across dynamic urban infrastructures. Existing orchestration mechanisms are typically rule-based and rely on low-level telemetry signals such as latency, node availability, or network conditions, limiting their ability to interpret the contextual meaning of system behavior and environmental events. This paper introduces Urban AI OS, a trustworthy LLM-based semantic control layer for distributed urban edge intelligence. The proposed architecture transforms heterogeneous telemetry and environmental signals into high-level semantic events through large language model reasoning, enabling context-aware orchestration decisions including adaptive topology management, workload coordination, and node role assignment. To address the reliability risks associated with LLM-assisted control, Urban AI OS employs confidence-gated execution with deterministic fallback policies, post-action monitoring, rollback, and auditable decision logging to constrain the operational impact of uncertain or erroneous LLM recommendations. By decoupling semantic reasoning from the data plane execution of AI workloads, Urban AI OS provides a model-agnostic framework for managing large-scale urban edge intelligence infrastructures. Experimental evaluation on a real-world urban IoT deployment with 50+ edge devices demonstrates that the proposed semantic operating layer improves system responsiveness by 35%, reduces unnecessary topology changes by 42%, and improves communication efficiency compared to conventional rule-based and adaptive threshold baselines, while maintaining confidence calibration through formal fallback mechanisms. Full article

Building construction sites are dynamic systems in which safety decisions interact with time, cost, productivity, equipment movement, and spatial constraints. This systematic review examines how building-construction-stage safety is represented in optimization-based and optimization-linked decision studies published between 1 January 2016 and 30 June 2026. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020-informed workflow used searches of the Web of Science Core Collection and IEEE Xplore, supplemented by Google Scholar and backward-citation checks. Seventy-nine studies met the core inclusion criterion, which required safety to appear as a quantified objective, constraint, evaluation metric, decision criterion, or prediction target. Studies were classified by problem type, safety role, method family, digital integration, and validation evidence. The synthesis identifies a problem-type-dependent formulation pattern: site-layout and scheduling studies mainly optimize safety or exposure objectives; crane/lifting studies distribute safety across constraints, objectives, and decision criteria; risk-decision studies use criteria or metrics; and prediction studies tune models whose targets are safety or risk outcomes. The core corpus is concentrated in site-layout and crane/lifting studies, whereas temporary works, monitoring-to-intervention, and construction-stage emergency response are less often formulated as optimization problems. Strict real-site/field evidence was identified in 7 of 79 studies, with an upper sensitivity bound of 11. Future research should prioritize transparent metrics, benchmarks, field validation, and closed-loop workflows. 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

Climate change is increasing the frequency of heat stress events in dairy farming, adversely affecting milk production, milk composition, cow behavior, and animal health. However, many previous studies relied on distant weather-station data and low-frequency milk recording systems, limiting the assessment of short-term and delayed heat stress responses. Therefore, the aim of this study was to combine dense longitudinal data from automatic milking systems (AMS) with continuously recorded on-farm meteorological measurements to investigate the immediate and lagged effects of heat stress on Holstein dairy cows. The study included 386,587 AMS visit records from 790 cows on three commercial dairy farms in Germany, corresponding to up to 127,310 cow-day records collected between August 2022 and August 2025. Temperature–humidity index (THI) values were calculated based on dense on-farm temperature and relative humidity records and were evaluated for multiple lag periods prior to AMS recordings. Linear mixed models were applied to infer the effects of THI on production, physiological, behavioral, and milking process traits. Increasing THI was associated with reduced daily milk yield, altered milk fat and protein percentages, decreased AMS visit frequency, prolonged milking intervals, and increased milk temperature. For contemporaneous THI, an increase from THI 50 to THI 70 corresponded to model-estimated declines of −0.86 kg in daily milk yield, −0.20% in milk fat content and −0.06% in milk protein content, −0.12 daily AMS visits, and +1.14 °C in milk temperature. The strongest associations were generally observed for prompt and short-term lagged THI windows. In contrast, longer lag periods were associated with weaker and less distinct trait responses. Rather than merely confirming the established decline in milk yield under heat stress, the integrated and temporally resolved analysis revealed trait-specific response patterns across production, behavioral, physiological, health-related, and milking-process traits. In particular, milk temperature and voluntary AMS attendance showed pronounced associations with contemporaneous and short-term THI, demonstrating the value of combining AMS-derived phenotypes with high-resolution on-farm climate data for heat stress monitoring. Full article

Post-hemorrhagic hydrocephalus (PHH) is a serious neurological sequela of severe intraventricular hemorrhage (IVH) in premature infants and remains one of the leading indications for ventriculoperitoneal (VP) shunt placement. Evaluating possible VP shunt-related complications can be challenging because clinical manifestations are often nonspecific, neuroimaging may initially appear unchanged, and microbiological cultures may remain negative. We report the case of a 19-month-old male born at 28 weeks’ gestation who developed Grade IV germinal matrix/intraventricular hemorrhage with bilateral intraparenchymal extension, early periventricular cystic leukomalacia, and post-hemorrhagic communicating hydrocephalus requiring multiple cerebrospinal fluid diversion procedures culminating in long-term VP shunt dependence. His medical history was notable for recurrent neonatal meningitis, secondary epilepsy with previous episodes of status epilepticus, secondary adrenal insufficiency, and severe global developmental delay. He presented with fever, recurrent coffee-ground vomiting, abdominal distension, progressive lethargy, reduced responsiveness, and localized erythematous swelling over the cranial VP shunt reservoir, raising concern for possible shunt-related pathology. During hospitalization, he deteriorated with status epilepticus and respiratory failure, with clinical concern for increased intracranial pressure, requiring admission to the Pediatric Intensive Care Unit (PICU). Laboratory investigations demonstrated leukocytosis, elevated C-reactive protein, cerebrospinal fluid pleocytosis, markedly elevated CSF protein, and CSF glucose of 2.0 mmol/L, for which a paired serum glucose value was unavailable, while repeated blood, urine, wound, and CSF cultures remained negative. Initial computed tomography (CT) demonstrated no significant interval change in the chronic hydrocephalus despite progressive neurological deterioration; however, serial neuroimaging later revealed progressive bilateral extra-axial fluid collections with radiological features suggestive of an evolving subacute subdural hemorrhage. The patient was managed with empirical broad-spectrum intravenous antibiotics, aggressive seizure control, stress-dose corticosteroids, respiratory support, and continuous multidisciplinary monitoring. His neurological and respiratory status subsequently improved, and he returned to his pre-admission neurological baseline before discharge with planned further evaluation at a tertiary pediatric neurosurgical center. This case highlights the diagnostic uncertainty surrounding acute neurological deterioration in a child with shunt-dependent PHH. VP shunt-related infection or malfunction remained important but unconfirmed diagnostic considerations, alongside competing or potentially overlapping contributors including status epilepticus, evolving extra-axial collections, respiratory infection, and endocrine or metabolic decompensation. No single etiology was definitively established. The case emphasizes the importance of serial neurological assessment, consideration of alternative diagnoses, repeat neuroimaging, and multidisciplinary evaluation when initial investigations do not establish the cause of deterioration. Full article

Through-going structures are widely distributed in rock masses of underground engineering, and their dip angles act as the core factor affecting the stress field and mechanical response of surrounding rock. To reveal the mechanical mechanism of rock masses containing through-going structures with different dip angles, this study adopts a combined method of theoretical derivation, indoor model testing and numerical simulation. Firstly, a plane strain mechanical model is established to classify Tectonically-induced Stress, Residual Gravitational Stress and engineering-induced stress, and the theoretical formulas for stress components, stress residual coefficient and stress deflection angle are derived. Secondly, rock-like specimens with through-going structures of various dip angles are prepared and biaxial compression tests are carried out to monitor mechanical parameters such as surrounding rock strain and peak strength. Finally, a large-scale numerical model is built by FLAC2D (version 7.0) software to simulate the whole process of stress equilibrium and excavation unloading of rock mass under a normal stress of 20 MPa. Then the data of principal stress, stress components, stress residual coefficient and deflection angle under different dip angles are extracted. The results show that the dip angle of through-going structure exerts a prominent regulatory effect on the rock mass stress field. With the increase of the dip angle, the Tectonically-induced Stress decreases continuously while the Residual Gravitational Stress rises gradually. The variation trend of stress deflection angle is highly consistent with structural dip angle, and the influence of Residual Gravitational Stress on deflection angle is limited. Due to the differences in loading modes and model sizes between indoor tests and numerical simulations, the evolution laws of stress residual coefficient show opposite trends, but both results verify the dominant effect of structural dip angle. Combined with theoretical, experimental and numerical results, the proposed theoretical system can effectively describe the stress evolution law of rock masses with through-going structures, which provides theoretical reference and technical support for the stability analysis of surrounding rock in similar underground engineering. Full article