Search Results (846)

Since the 1960s, theories on the relationship between people and their environment have explored how elements of the built environment may directly or indirectly influence human behavior. In this context, neuroarchitecture is emerging as an interdisciplinary field that integrates neuroscience, architecture, environmental psychology, and cognitive science, with the aim of providing empirical evidence on how architectural spaces affect the human brain. This study investigates the potential of neuroarchitecture to inform environmental design by clarifying its current conceptual framework, examining its practical applications, and identifying the context in which it is being implemented. Beginning with an in-depth analysis of the definition of neuroarchitecture, its theoretical foundations, and the range of interpretations within the academic community, the study then offers a critical review of its practical applications across various design fields. By presenting a comprehensive overview of this emerging discipline, the study also summarizes the measurement techniques commonly employed in related research and critically evaluates design criteria based on observed human responses. Ultimately, neuroarchitecture represents a promising avenue for creating environments that deliberately enhance psychological and physiological well-being, paving the way toward truly human-centered design. Nevertheless, neuroarchitecture is still an emerging experimental field, which entails significant limitations. The experiments conducted are still limited to virtual reality and controlled experimental contexts. In addition, small and heterogeneous population samples have been tested, without considering human variability. Full article

Background/Objectives: Incomplete spinal cord injury (iSCI) represents a significant challenge in neurorehabilitation, with conventional limitations including recovery plateaus and declining patient motivation. Virtual reality (VR) and augmented reality (AR) have emerged as promising technologies to supplement traditional therapy through gamification and multisensory feedback. This systematic review and meta-analysis evaluates the effectiveness of VR and AR interventions for improving balance and locomotor function in patients with incomplete spinal cord injury. Methods: A systematic review was conducted following PRISMA guidelines, with searches in PubMed, Scopus, Web of Science, Science Direct, and Google Scholar. Randomized controlled trials and high-quality controlled studies evaluating VR/AR interventions in patients with iSCI (American Spinal Injury Association Impairment Scale [AIS] classifications B, C, or D) for a minimum of 3 weeks were included. A random-effects meta-analysis (Standardized Mean Difference, SMD; 95% Confidence Interval, CI) was conducted for the balance outcome. Results: Eight studies were included (n = 142 participants). The meta-analysis for balance (k = 5 studies) revealed a statistically significant improvement with a large effect size (SMD = 1.21, 95% CI: 0.04–2.38, p = 0.046). For locomotor function, a quantitative meta-analysis was not feasible due to a limited number of methodologically homogeneous studies; a qualitative synthesis of this evidence remained inconclusive. Substantial heterogeneity was observed in the balance analysis (I² = 81.5%). No serious adverse events related to VR/AR interventions were reported. Conclusions: VR/AR interventions show potential as an effective adjunctive therapy for improving balance in patients with iSCI, though the benefit should be interpreted with caution due to considerable variability between studies. The current evidence for locomotor function improvements is insufficient to draw conclusions, highlighting a critical need for more focused research. Substantial heterogeneity indicates that effectiveness may vary according to specific intervention characteristics, populations, and methodologies. Larger multicenter studies with standardized protocols are required to establish evidence-based clinical guidelines. Full article

The digital transformation of civic life has created new opportunities for older adults to engage in virtual volunteer activities. However, their participation still remains limited. This study investigates the factors that influence older adults’ interest in virtual volunteering. It integrated theoretical framework combining the Technology Acceptance Model (TAM), Self-Efficacy, and Digital Divide Theories to examine the drivers of virtual volunteerism interest among this target population. This study presents ordered logistic regression models with data on 814 adult volunteers in multiple imputation procedures. The final reduced model identifies two key predictors: a preference for virtual activities and interest in technology training, respectively, representing TAM and the Digital Divide Theory. While the self-efficacy-related variable showed statistical significance in earlier models, its explanatory power diminished when controlling for other factors. The findings indicate that older adults’ interest in virtual volunteering is primarily shaped by perceived usefulness of digital tools and their willingness to improve technical competence. This study confirms the relevance of the TAM and Digital Divide theories regarding virtual volunteerism. In practical terms, the findings indicate that program design should combine usability-focused platform features and targeted support that lower both technological and motivational barriers for older adults interested in virtual volunteering. Full article

Modern healthcare systems are under growing strain from aging populations, urbanization, and rising chronic disease burdens, creating an urgent need for real-time monitoring and informed decision-making. This survey examines how the convergence of Integrated Sensing and Communication (ISAC) and digital-twin technologies can meet that need by analyzing how ISAC unifies sensing and communication to gather and transmit data with high timeliness and reliability and how digital-twin platforms use these streams to maintain continuously updated virtual replicas of patients, devices, and care environments. Our synthesis compares ISAC frequency options across sub-6 GHz, millimeter-wave, and terahertz bandswith respect to resolution, penetration depth, exposure compliance, maturity, and cost, and it discusses joint waveform design and emerging 6G architectures. It also presents reference architecture patterns that connect heterogeneous clinical sensors to ISAC links, data ingestion, semantic interoperability pipelines using Fast Healthcare Interoperability Resources (FHIR) and IEEE 11073, and digital-twin synchronization, and it catalogs clinical and operational applications, together with validation and integration requirements. We conduct a targeted scoping review of peer-reviewed literature indexed in major scholarly databases between January 2015 and July 2025, with inclusion restricted to English-language, peer-reviewed studies already cited by this survey, and we apply a transparent screening and data extraction procedure to support reproducibility. The survey further reviews clinical opportunities enabled by data-synchronized twins, including personalized therapy planning, proactive early-warning systems, and virtual intervention testing, while outlining the technical, clinical, and organizational hurdles that must be addressed. Finally, we examine workflow adaptation; governance and ethics; provider training; and outcome measurement frameworks such as length of stay, complication rates, and patient satisfaction, and we conclude that by highlighting both the integration challenges and the operational upside, this survey offers a foundation for the development of safe, ethical, and scalable data-driven healthcare models. Full article

With the rapid development of Industry 5.0, smart manufacturing has become a key focus in production systems. Hence, achieving efficient planning and scheduling on the shop floor is important, especially in job shop environments, which are widely encountered in manufacturing. However, traditional job shop scheduling problems (JSP) assume fixed operation sequences, whereas in modern production, some operations exhibit sequence flexibility, referred to as sequence-free operations. To mitigate this gap, this paper studies the JSP with discrete operation sequence flexibility (JSPDS), aiming to minimize the makespan. To effectively solve the JSPDS, a mixed-integer linear programming model is formulated to solve small-scale instances, verifying multiple optimal solutions. To enhance solution quality for larger instances, a digital twin (DT)–enhanced initialization method is proposed, which captures expert knowledge from a high-fidelity virtual workshop to generate high-quality initial population. In addition, a statistical learning-assisted local search method is developed, employing six tailored search operators and Thompson sampling to adaptively select promising operators during the evolutionary algorithm (EA) process. Extensive experiments demonstrate that the proposed DT-statistical learning EA (DT-SLEA) significantly improves scheduling performance compared with state-of-the-art algorithms, highlighting the effectiveness of integrating digital twin and statistical learning techniques for shop scheduling problems. Specifically, in the Wilcoxon test, pairwise comparisons with the other algorithms show that DT-SLEA has p-values below 0.05. Meanwhile, the proposed framework provides guidance on utilizing symmetry to improve optimization in complex manufacturing systems. Full article

Background/Objectives: Subarachnoid cysts in children, while often linked to trauma, can also rupture spontaneously without any apparent injury. Their etiology remains complex, involving congenital, traumatic, and infectious factors. This article explores the risks, pathophysiology, and management strategies related to spontaneous rupture in pediatric cases reported in the literature through the means of a systematic review. Materials and Methods: A systematic review of Web of Science, Scopus, PubMed and the Virtual Health Library (BVS, for its acronym in Spanish) was conducted; the online software Ryyan was used to manage the references and conduct the filtering process. The National Heart, Lung, and Blood Institute (NHLBI) quality assessment tool was used to assess bias for each type of study. Results: We analyzed the data of 101 articles; in total we found that 331 pediatric patients with arachnoid cyst were diagnosed with intracranial hemorrhage and 1030 patients had an unruptured arachnoid cyst. The most common cyst diameter was between 5–7 cm in the bleeding group vs. 3–4.5 cm in the non-bleeding group. A head trauma trigger was identified in 36.25% of cases of bleeding and 10.6% were sports related. Most of the hemorrhages were subdural, followed by a mixed pattern between subdural and intracystic. In both groups the arachnoid cyst was mostly located in the middle cranial fossa in the left side. The bleeding arachnoid cysts were mostly treated with surgery, but conservative treatment was also effective; the outcome was good in the majority of cases. Conclusions: Further research is required to elucidate the pathophysiological mechanisms underlying hemorrhage associated with arachnoid cysts in the pediatric population. Nevertheless, upon identification of an arachnoid cyst, neurosurgical follow-up is warranted. Bleeding tends to occur only in the presence of high-risk features and can be precipitated by traumatic events. Full article

Introduction. Adverse drug events (ADEs) are between the third and sixth most common cause of death worldwide. Biosimulation studies performed using real-world data could generate relevant drug safety information without exposing patients to ADEs. Methods. Iclepertin (BI-425809) was virtually added to the actual drug regimens of n = 4,405,063 individuals. Changes in risk level were estimated for drug-induced long QT syndrome and CYP450 drug interactions. The properties used for iclepertin included: dose of 10 mg (oral) once daily; bioavailability (F) = 71%; Cmax of 222 nM; CYP3A4 weak affinity substrate (partial metabolic clearance of ~80%); IC₅₀ for hERG block of 30 μM. Results. A change in total medication risk score (MRS) was observed (6.3 ± 6.6 to 7.2 ± 6.6) following the addition of iclepertin in ~50% (n = 2,138,247) of the studied population. Among individuals with a change in MRS, ~65% had a 2-unit increase (max 11 units). The number of individuals classified in the High/Severe MRS category increased by 0.33%. The addition of iclepertin to individuals receiving CYP3A4 perpetrator drugs produced a greater change in MRS (+1.5) when compared to individuals not exposed to CYP3A4 perpetrators (+0.8). An additional 0.0032% of the population (n = 139) would be at risk of QT prolongation following the intake of iclepertin. Subset analyses performed in individuals with schizophrenia (targeted indication) demonstrated that these individuals had higher MRS values (13.0 ± 10.3) compared to those without schizophrenia (6.2 ± 6.9). However, the addition of iclepertin did not produce a greater increase in MRS in the schizophrenia population vs. the control population. Our pharmacoeconomic model did not account for any beneficial effects of the drug but the model based on MRS changes predicted a USD 91 yearly increase in medical expenditures (emergency department visits and hospitalizations) per individual (USD 3172 to USD 3263) following the addition of iclepertin. A similar increase was observed in the schizophrenia population following iclepertin addition. Conclusions. The increase in MRS associated with the addition of iclepertin to the drug regimen of a large population was minimal and mostly driven by CYP3A4 interactions. Using this model, interactions can be identified a priori, making risk mitigable and preventable without exposing patients to toxicity. Full article

The current agent-based evolutionary models for animal communication rely on simplified signal representations that differ significantly from natural vocalizations. We propose a novel agent-based evolutionary model based on text-to-audio (TTA) models to generate realistic animal vocalizations, advancing from VAE-based real-valued genotypes to TTA-based textual genotypes that generate bird songs using a fine-tuned Stable Audio Open 1.0 model. In our sexual selection framework, males vocalize songs encoded by their genotypes while females probabilistically select mates based on the similarity between males’ songs and their preference patterns, with mutations and crossovers applied to textual genotypes using a large language model (Gemma-3). As a proof of concept, we compared TTA-based and VAE-based sexual selection models for the Blue-and-white Flycatcher (Cyanoptila cyanomelana)’s songs and preferences. While the VAE-based model produces population clustering but constrains the evolution to a narrow region near the latent space’s origin where reconstructed songs remain clear, the TTA-based model enhances the genotypic and phenotypic diversity, drives song diversification, and fosters the creation of novel bird songs. Generated songs were validated by a virtual expert using the BirdNET classifier, confirming their acoustic realism through classification into related taxa. These findings highlight the potential of combining large language models and TTA models in agent-based evolutionary models for animal communication. Full article

Lung cancer is one of the most common and socially significant cancers worldwide and consists of two main subtypes: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which require different treatments. Computed tomography (CT) scans cannot reliably differentiate these subtypes, often necessitating invasive biopsies that carry significant risks. Radiomics offers a promising non-invasive alternative by quantitatively analyzing imaging data to extract detailed tissue characteristics beyond visual assessment. This pilot retrospective study analyzed 200 Moscow patients with histologically confirmed SCLC or NSCLC. Manual tumor segmentation on pretreatment CT scans allowed extraction of 107 radiomic features, from which 16 key features were selected to train four machine learning models. Models were evaluated using stratified 5-fold cross-validation, focusing on ROC AUC, accuracy, precision, and recall. All models demonstrated strong performance in distinguishing SCLC from NSCLC, with the gradient boosting model achieving the highest accuracy of 80.5% and ROC AUC of 0.888. These results highlight the potential of radiomics combined with machine learning to enable accurate, non-invasive differentiation of lung cancer subtypes. Further research is needed to expand feature sets, develop automated segmentation tools, and enhance clinical application of this approach. Full article

Virtual reality (VR) technology has emerged as a promising alternative to conventional perimetry for assessing visual fields. However, the clinical validity of commercially available VR-based perimetry devices remains uncertain due to variability in hardware, software, and testing protocols. A systematic review was conducted following PRISMA guidelines to evaluate the validity of VR-based perimetry compared to the Humphrey Field Analyzer (HFA). Literature searches were performed across MEDLINE, Embase, Scopus, and Web of Science. Studies were included if they assessed commercially available VR-based visual field devices in comparison to HFA and reported visual field outcomes. Devices were categorized by regulatory status (FDA, CE, or uncertified), and results were synthesized narratively. Nineteen studies were included. Devices such as Heru, Olleyes VisuALL, and the Advanced Vision Analyzer showed promising agreement with HFA metrics, especially in moderate to advanced glaucoma. However, variability in performance was observed depending on disease severity, population type, and device specifications. Limited dynamic range and lack of eye tracking were common limitations in lower-complexity devices. Pediatric validation and performance in early-stage disease were often suboptimal. Several VR-based perimetry systems demonstrate clinically acceptable validity compared to HFA, particularly in certain patient subgroups. However, broader validation, protocol standardization, and regulatory approval are essential for widespread clinical adoption. These devices may support more accessible visual field testing through telemedicine and decentralized care. Full article

The global demographic transition toward an ageing population has necessitated substantive reforms in dental education, particularly within the field of geriatric prosthodontics. Conventional curricula have frequently prioritized technical competencies while insufficiently addressing the integration of biological, psychosocial, and ethical complexities inherent in the care of older adults. This scoping review critically examined these curricular deficiencies by synthesizing evidence from 34 peer-reviewed studies, employing Bloom’s Taxonomy as a conceptual framework to inform a systematic and pedagogically grounded curriculum redesign. The primary aim was to identify existing gaps in undergraduate and postgraduate education, evaluate the efficacy of active and simulation-based learning modalities, assess the utility of reflective practices and standardised assessment tools, and formulate strategic, taxonomy-aligned pedagogical guidelines. Following the PRISMA-ScR methodology, the included studies were thematically analysed and categorized across the six cognitive levels of Bloom’s Taxonomy. Findings highlighted the effectiveness of integrated educational strategies, including Case-Based Learning, interprofessional education, virtual simulations, and structured assessments such as Objective Structured Clinical Examinations (OSCE). Furthermore, reflective models such as “What? So What? Now What?” fostered higher-order cognitive processes, ethical reasoning, and self-directed learning. By aligning cognitive levels—from foundational knowledge recall to innovative creation—ten evidence-based educational guidelines were developed. These guidelines are pedagogically sound, empirically supported, and adaptable to diverse curricular contexts. The proposed framework ensures a deliberate, progressive trajectory from theoretical comprehension to clinical expertise and ethical leadership. Future research should explore longitudinal outcomes and develop scalable, culturally responsive models to support the broader implementation of curricular reform in geriatric dental education. Full article

(1) Background: The convergence of digital twin technology, artificial intelligence, and multimodal biomarkers heralds a transformative era in neuropsychological assessment and intervention. Digital twin cognition represents an emerging paradigm that creates dynamic, personalized virtual models of individual cognitive systems, enabling continuous monitoring, predictive modeling, and precision interventions. This systematic review comprehensively examines the integration of AI-driven biomarkers within biomimetic neuropsychological frameworks to advance personalized cognitive health. (2) Methods: Following PRISMA 2020 guidelines, we conducted a systematic search across six major databases spanning medical, neuroscience, and computer science disciplines for literature published between 2014 and 2024. The review synthesized evidence addressing five research questions examining framework integration, predictive accuracy, clinical translation, algorithm effectiveness, and neuropsychological validity. (3) Results: Analysis revealed that multimodal integration approaches combining neuroimaging, physiological, behavioral, and digital phenotyping data substantially outperformed single-modality assessments. Deep learning architectures demonstrated superior pattern recognition capabilities, while traditional machine learning maintained advantages in interpretability and clinical implementation. Successful frameworks, particularly for neurodegenerative diseases and multiple sclerosis, achieved earlier detection, improved treatment personalization, and enhanced patient outcomes. However, significant challenges persist in algorithm interpretability, population generalizability, and the integration of healthcare systems. Critical analysis reveals that high-accuracy claims (85–95%) predominantly derive from small, homogeneous cohorts with limited external validation. Real-world performance in diverse clinical settings likely ranges 10–15% lower, emphasizing the need for large-scale, multi-site validation studies before clinical deployment. (4) Conclusions: Digital twin cognition establishes a new frontier in personalized neuropsychology, offering unprecedented opportunities for early detection, continuous monitoring, and adaptive interventions while requiring continued advancement in standardization, validation, and ethical frameworks. Full article

Background: Dentophobia, a significant barrier to dental healthcare, may be influenced by an increased dependency on digital technology and internet addiction, particularly among younger populations. This study aimed to assess the effectiveness of Virtual Reality Exposure Therapy (VRET) compared to traditional methods in managing dentophobia, particularly among individuals exhibiting high levels of internet dependency. Methods: A comparative study involving two groups, each consisting of 50 young adults aged 18–30 years, diagnosed with dentophobia, was conducted. Group A participants, who exhibited high familiarity and borderline addictive behavior towards digital technologies, received VRET using VR-BOX glasses across four specific dental scenarios: dental chair positioning, oral examination, anesthesia administration, and dental drilling procedures. Group B received traditional “tell–show–do” management without VR assistance. Anxiety levels were evaluated using the Modified Dental Anxiety Scale (MDAS) before and after interventions and at follow-up intervals of one week, three months, and six months. Results: Both groups showed significant reductions in anxiety scores across all follow-up periods. Mild to phobic anxiety scores demonstrated no significant differences between VRET and traditional method groups. The average MDAS scores post-intervention were similar, indicating comparable effectiveness between both treatment modalities. Conclusions: Virtual Reality Exposure Therapy effectively reduces dentophobia among young adults, particularly those with significant internet dependency. Although VRET’s effectiveness was similar to conventional methods, it holds considerable promise for improving treatment adherence and comfort among digitally dependent individuals. Full article

Background: Spatial navigation is one’s ability to travel through their environment to reach a goal location. Self-expansion is the motivation to increase one’s self-perception through engaging in novel activities. Our objective was to examine the relations among self-expansion, age, and navigation ability and investigate how one’s internal motivation may influence navigation performance across paradigms. Methods: In total, 33 younger adults (YAs; 19F, 14M, mean age = 25.0 ± 1.6) and 74 older adults (OAs; 52F, 22M, mean age = 69.5 ± 8.0) completed the following: Self-Expansion Preference Scale (SEPS), Wayfinding Questionnaire (WQ), Virtual Supermarket Task, Virtual Morris Water Maze (vMWM), and a Floor Maze Task (FMT). Mann–Whitney U tests and Spearman ρ correlations were used to examine differences in navigation performance between YAs vs. OAs and self-expanders vs. self-conservers, and relations among the measures, respectively. Results: YAs had lower vMWM completion times compared to OAs (p < 0.001). Self-expanders had better recall of the vMWM environment compared to self-conservers (p = 0.049), independent of age. Greater self-expansion in YAs was correlated with lower spatial anxiety (ρ = −0.356, p = 0.042) and faster completion of the FMT (ρ = −0.36, p = 0.042). Discussion: Our results build on established age-related deficits in navigation abilities to identify correlations of self-expansion and better performance in various navigation tasks. Independent of age, individuals with greater inclination towards self-expansion exhibit superior navigation abilities. Future research should explore underlying mechanisms driving these associations and investigate intervention strategies aimed at improving navigation skills in aging populations through increasing self-expansion. Full article

Objectives: Tonsillectomy is among the most frequently performed pediatric ENT procedures. Post-tonsillectomy pain and hemorrhage remain key determinants of postoperative morbidity and may differ by surgical technique. This work’s objective is to compare postoperative pain, bleeding, and operative duration across three pediatric tonsillectomy techniques: cold dissection with suturing, cold dissection with ligation, and hot dissection with bipolar cautery. Materials and Methods: In this single-center, prospective study, 150 children (n = 50 per group) undergoing tonsillectomy (with adenoidectomy) between October 2022 and October 2024 were assigned preoperatively to the following groups: Group 1—cold dissection + suturing; Group 2—cold dissection + ligation; Group 3—hot dissection (bipolar cautery). Pain was assessed with the Wong–Baker FACES scale at 1, 6, and 24 h, days 3 and 7, and with the Parents’ Postoperative Pain Measure (PPPM) at 1, 6, and 24 h. Primary bleeding was defined within 24 h; secondary bleeding was within 2 weeks. Operative time was recorded from first incision to hemostasis. Non-parametric tests and chi-square analyses were used with p < 0.05 considered significant. Results: Of 150 patients, 58% were male. No primary hemorrhage occurred. Secondary hemorrhage occurred in 4/150 (2.7%): 1/50 (2%) in Group 1, 0/50 (0%) in Group 2, and 3/50 (6%) in Group 3 (overall p > 0.05). Readmission for oral-intake difficulty occurred in 4/150 (2.7%): 1/50 (2%) in Group 1 and 3/50 (6%) in Group 3 (p > 0.05). Operative time differed significantly across groups (Kruskal–Wallis p < 0.05), being longest in Group 1 and shortest in Group 3 (17.53 ± 1.26 min); Group 2 averaged 18.60 ± 0.94 min and Group 1 21.89 ± 1.64 min. Pain decreased over time in all groups (Friedman p < 0.001). Across virtually all time points, Group 2 (ligation) had significantly lower Wong–Baker and PPPM scores than Groups 1 and 3 (Dunn post-hoc, adjusted p < 0.05), while Groups 1 and 3 did not differ consistently. Conclusions: Cold dissection with ligation yielded the most favorable pain profile while maintaining low bleeding rates; hot dissection minimized operative time but tended toward higher secondary bleeding and postoperative intake difficulties. Technique selection should prioritize postoperative comfort and morbidity reduction—particularly in pediatric populations—favoring cold dissection, with ligation offering a consistent analgesic advantage. Full article