Abstract: Orthodontic treatment can be safely performed during pregnancy when tailored to the patient’s hormonal, physiological, psychological, and oral health changes. The study aims to establish a safe, trimester – specific orthodontic protocol that minimizes maternal – foetal risks while ensuring effective treatment. A systematic PubMed search using combined keywords and subtopic – specific queries was performed to identify relevant literature on orthodontics during pregnancy. Most studies were literature reviews, followed by various observational, survey – based, clinical, and case report designs. Orthodontic care during pregnancy must be adapted to trimester – related risks, with minimal interventions in the first trimester, elective procedures in the second, comfort focused management in the third, and treatment of complex care postpartum. This protocol requires individual adaptation, highlighting the need for personalized medicine and coordinated input from multiple specialists to address orthodontic, obstetric, and psychological factors during pregnancy.

Abstract: Structural vibration is a significant problem created by industrial machinery (i.e., compressors, motors, and generators) that can negatively affect the performance of equipment as well as the overall integrity of buildings or structures. Although various vibration isolation technologies are available for reducing the structural vibrations produced by machinery, most of these methods have inherent limitations because of a lack of sufficient damping at lower frequencies relative to that observed higher frequency ranges. The purpose of this paper is to evaluate the use of advanced vibration isolation technologies using re-entrant auxetic structures that are characterized by their negative Poisson ratios. Through a comprehensive evaluation of 92 published articles within the areas of auxetic unit cell design and topology optimization, the mechanics of materials related to negative Poisson ratios, energy absorption mechanisms, vibration reduction in sandwich structures, and dynamic analyses of frame and plate systems, this review presents the current state-of-the-art re-entrant auxetic structures that can be employed as vibration isolation technologies for machine foundations. The analysis reveals that compared with standard structures, re-entrant geometry-based structures exhibit high levels of energy absorption (up to a 767% increase over the standard designs), along with superior vibration isolation characteristics. A hybrid approach utilizing combinations of geometric modification, multimaterial fabrication, and foam filling is identified as the most promising method for optimizing the relationship between stiffness and damping capacity. Additionally, advancements in additive manufacturing have made it possible to fabricate complex auxetic geometries that were previously unfeasible via traditional processes. In addition to identifying significant research gaps, such as scaling up to large macroscale steel implementations, this paper presents general design guidelines for future vibration isolation systems for industrial machinery.

Abstract: The theoretical construction of traditional quantum acoustics is based on the core presupposition that "microscopic structures must be described by quantum mechanics". This presupposition has not been directly verified, and its core concept, the "phonon", is defined as a quasi-particle with energy E=hν. This paper systematically reexamines the conceptual foundations of quantum acoustics based on the "Revised Energy Quantum Concept" – i.e., the "measurement discreteness" of energy transfer rather than "physical discreteness". Drawing on the radiation mechanism of an electron's variable-speed motion around the nucleus (which clearly distinguishes the orbital frequency from the radiation frequency), this paper further clarifies that the natural frequency of crystal lattice vibration (the frequency of atomic motion around equilibrium positions) and the energy radiation/absorption frequency are two independent physical quantities. They are connected through the "frequency change quantity". The interaction between high-frequency sound waves and the lattice is essentially a classical continuous dynamics process. "Phonons" are not particles with physical reality but are discrete measurement units for changes in the excitation strength of lattice vibration modes. Starting from first principles and based on the core mechanism of "frequency change triggering energy exchange", this paper rigorously derives the zero-point energy formula, pointing out that zero-point energy essentially characterizes the dynamic ground-state energy scale of a system under the constraint of the minimum energy measurement unit ε. Using Raman scattering as an example, quantitative calculations of energy transfer involving the revised energy quantum εare supplemented, clarifying the physical meaning differences between ε and h. The study shows that all quantum acoustics phenomena can be interpreted and verified more clearly and self-consistently within a classical continuous dynamics framework, providing a theoretically solid and physically intuitive path for the field.

Abstract: The COVID-19 pandemic intensified faculty emotional labor as instructors were expected to sustain learning while responding to students’ grief, isolation, and uncertainty. Educa-tional leadership educators occupy a distinctive role as mentors and models for current and aspiring PK–12 and higher education leaders. Using a secondary phenomenological analysis, we reanalyzed de-identified Zoom interview transcripts (2022) from nine U.S. educational leadership educators (seven women; four educators of color) originally col-lected to examine caring pedagogies. Guided by Hochschild’s emotional labor theory and feminist care ethics, with particular attention to Tronto’s political theory of care, we con-ducted a theoretically informed thematic analysis focused on caring expectations, role boundaries, and well-being. Findings highlight five interrelated themes: serving as an “anchor” during crisis; blurred instructional–counseling roles and invisible care work; gendered and racialized expectations of availability; competing care obligations across work and home; and boundary-setting as resistance and sustainability. Participants de-scribed deep relational commitments to students alongside exhaustion, role strain, and frustration with institutional cultures that assumed limitless capacity to care without re-ciprocal support. Emotional labor in leadership education should be recognized as central leadership work, and sustainable cultures of care require systemic policies that redistrib-ute and resource care labor.

Abstract: Critical congenital heart disease (CCHD) is a major cause of neonatal morbidity and mortality. Pulse oximetry screening enables early detection, potentially reducing complications and improving outcomes. This study evaluated pediatric residents’ knowledge, attitudes, and practices (KAP) related to CCHD screening in Saudi Arabia. Methods: A cross-sectional survey was distributed to pediatric residents across Saudi Arabia. The questionnaire assessed knowledge, attitude, and practice regarding CCHD screening. Results: A total of 123 pediatric residents in training were included in the study. Of these, 57 (46.3%) were male, and 66 (53.7%) were female. A progressive increase in mean scores was observed with advancing training years (p = 0.010). A significant difference was observed in knowledge scores based on completion of a cardiology rotation (p = 0.006). A progressive increase in attitude scores was observed with each successive year of training. Current year in training showed a statistically significant association with attitude scores (p < 0.001). Completion of a newborn nursery or NICU rotation was also significantly associated with higher attitude scores (p = 0.027). Similarly, attitude scores were significantly higher among those who had completed a cardiology rotation (mean = 12.99, SD = 1.52) compared to those who had not (mean = 11.60, SD = 1.84; p < 0.001). While practice scores were not statistically different across most groups, senior residents demonstrated better adherence to screening. Conclusions: Residents exhibit increasing awareness and positive attitudes with experience; however, practical implementation remains inconsistent. Targeted education and standardized protocols are necessary to improve outcomes. A positive correlation was observed between knowledge and attitude scores (r = 0.346, p < 0.001).

Abstract: The main objective of this study is to automatically detect real-time snow-related road-surface conditions utilizing existing webcams along interstate freeways. Blowing snow is considered one of the most critical road surface conditions, causing vertigo and adversely affecting vehicle performance. A comprehensive image reduction process was performed to extract two distinct reference datasets. The first dataset comprised two image categories: blowing snow and no blowing snow, while the second dataset consisted of five categories: blowing snow, dry, slushy, snow-patched, and snow-covered. Six pre-trained convolutional neural networks (CNN) were utilized for road-surface condition classification: AlexNet, SqueezeNet, ShuffleNet, ResNet18, GoogleNet, and ResNet50. In Dataset 1, it was concluded that AlexNet is a superior model with respect to training time and 97.56% overall detection accuracy. Regardless of differences in training time, ResNet50 achieved the highest overall accuracy of 97.88%, as well as the highest recall and F1-score. In Dataset 2, the ResNet18 model achieved an optimal overall detection accuracy of 96.10%, while the AlexNet model demonstrated the shortest training time and an overall detection accuracy of 95.88%. In addition, a comprehensive comparison was conducted between pre-trained CNNs and traditional machine learning models, with the former displaying significantly superior detection performance. Analysis of the confusion matrices revealed that AlexNet performed the best in detecting blowing snow events. The proposed models could automatically provide real-time accurate and consistent surface condition information.

Abstract: This study examines the value of user natural language feedback in adjusting recommendation strategies for mental health applications and its synergistic effect with behavioral data. We collected 500,000 natural language feedback entries (including subjective experiences, emotional descriptions, and task reflections) alongside corresponding behavioral logs. A joint vector space was constructed integrating linguistic content features and behavioral characteristics, analyzing relationships among feedback types, emotional tendencies, and usage behaviors.In recommendation experiments, language feedback was integrated into strategy updates and compared against a baseline behavioral model (clicks, session duration, completion rate). Results showed that models incorporating language feedback achieved a 19.7% increase in user satisfaction metrics, a 22.4% rise in recommended content completion rate, and a 13.2% decrease in negative feedback rate.Further analysis revealed that users exhibiting negative emotional fluctuations relied more heavily on linguistic feedback to guide content selection, while user groups with weaker behavioral data demonstrated significant gains under this model. The study indicates that natural language feedback complements subjective information uncaptured by behavioral data, aiding in the development of more supportive mental health recommendation systems.

Abstract: Feline pulmonary carcinomas are rare and often carry a poor prognosis, particularly when associated with feline lung–digit syndrome. We report a cat with primary pulmonary carcinoma and extensive metastases—including digits, pleura, mandible, scapula, spleen, skeletal muscle, and distant lymph nodes—supporting the broader “MODAL syndrome” concept. Adjuvant therapy with toceranib phosphate and meloxicam achieved prolonged survival and excellent quality of life, with no adverse effects despite dose escalation. Rapid progression after discontinuation suggests a role for toceranib in delaying tumour growth. Immunohistochemistry revealed c-kit expression in one metastatic lesion but not in the primary tumour or most metastases, highlighting intratumoral heterogeneity and the complexity of targeted therapy. The observed benefit likely reflects toceranib’s multi-target activity (VEGFR2, PDGFR), impacting angiogenesis and tumour progression. This case represents the first report of toceranib use in feline pulmonary carcinoma and underscores its potential as a palliative option.

Abstract: Quantum entanglement is a fundamental resource in quantum information theory, yet its general characterization and quantification remain challenging, especially in multipartite systems. In this work we investigate entanglement from a geometric perspective, focusing on the Riemannian structure induced by the Fubini--Study metric on the projective Hilbert space of multi-qubit quantum states. By exploiting the local-unitary invariance of this metric, we derive the entanglement distance (ED), a geometric measure that quantifies entanglement as an obstruction to locally minimizing the sum of squared Fubini--Study distances generated by local operations. We analyze the properties of ED for pure multi-qubit states and discuss its behavior under local operations and classical communication. In particular, we show that ED reproduces established entanglement measures in well-defined and restricted settings. For pure states of two qubits, ED reduces to an exact monotone function of the concurrence and, independently, to an explicit monotone function of the entropy of entanglement. These results provide a clear geometric interpretation of standard bipartite entanglement measures within the present framework, while highlighting the limitations of such correspondences beyond the two-qubit case.

Abstract: Multi-Group Homomorphic Encryption (MGHE) is a pivotal advance in secure multi-party computation, integrating merits of Multi-Party Homomorphic Encryption (MPHE) and Multi-Key Homomorphic Encryption (MKHE) to eliminate MPHE’s fixed-party limitation and mitigate MKHE’s ciphertext expansion from dynamic enrollment. However, the efficient single-key FINAL scheme cannot extend to multi-party scenarios, due to the challenge of defining valid multiplication for vector NTRU ciphertexts, which hinders its use in multi-group bootstrapping and curbs efficiency. To address this, additive secret sharing is adopted to convert vector NTRU ciphertext multiplication into secret share multiplication, enabling shared bootstrapping key generation within groups. For the first time, a multi-group ciphertext bootstrapping algorithm based on LWE and NTRU is proposed. Bootstrapping tasks are decomposed for parallel processing, and a hybrid product algorithm is designed to aggregate subtask outputs, boosting multi-group bootstrapping speed to match that of single-key ciphertexts. Noise accumulation is analyzed, with 100-bit and 128-bit security parameter sets selected for validation. Experiments show that 30/50-party multi-group bootstrapping takes only 1.87/2.58 seconds respectively.

Abstract: Human papillomavirus (HPV) infection remains a major global health concern due to its strong association with cervical and other anogenital and oropharyngeal cancers. The outcome of HPV infection is largely determined by complex interactions between the virus and host immune responses. This review summarizes current knowledge on the immune landscape of HPV infection, focusing on innate immune recognition, adaptive immune responses, and viral immune evasion strategies. HPV is sensed by host pattern recognition receptors, yet it efficiently suppresses interferon signaling and cytokine responses to establish persistent infection. Adaptive immunity, including HPV-specific CD4⁺ and CD8⁺ T-cell responses and neutralizing antibodies, plays a critical role in viral clearance, while defects in these responses contribute to persistence and disease progression. The virus employs multiple immune evasion mechanisms, such as downregulation of antigen presentation and modulation of cytokine signaling, facilitating immune escape and oncogenesis. The review also highlights immune correlates of protection, vaccine-induced immunity, and emerging immunotherapeutic strategies targeting HPV-associated diseases. A comprehensive understanding of HPV–host immune interactions is essential for optimizing vaccine design, improving therapeutic interventions, and reducing the global burden of HPV-related malignancies.

Abstract: This paper introduces a hybrid framework for assessing the technical feasibility and system readiness of emerging multimodal mobility concepts, with a focus on the Pods4Rail project. The methodology combines qualitative and quantitative approaches to address the inherent uncertainty of early design phases. The qualitative component evaluates Technology Readiness Levels (TRLs) for individual subsystems using expert judgment and visual heat maps, identifying critical challenges in automation, digitalization, and sustainability. The quantitative approach distinguishes between the probabilistic model—representing the uncertainties in TRL and IRL—the problem of propagating these uncertainties to estimate the System Readiness Level (SRL), and the algorithm used to solve this problem, which in this case is Monte Carlo simulation. This framework enables SRL estimation under uncertainty, where explicit quantification of uncertainties is essential for sound decision-making. Results indicate that Pods4Rail project currently falls between SRL 1 and SRL 2, corresponding to concept refinement and technology development stages. While subsystems such as the Transport Unit and Rail Carrier Unit exhibit higher maturity, planning and logistics remain less developed. By combining interpretative insights with statistical rigor, this framework provides a comprehensive readiness assessment and supports informed decision-making for future integration and risk management. The proposed approach is transferable to other innovative mobility systems facing similar challenges in early development stages.

Abstract:

This paper explores a new paradox in special relativity, examining implications for our understanding of the universe’s age. The paradox involves a spaceship traveling towards a planet; light signals are exchanged when they are 10 light-years apart. The signals meet after 5 years from the planet’s perspective, but the distance from the spaceship to the meeting point is less than 5 light-years. A solution exists which will prompt a re-evaluation of Einstein’s demonstration of non-simultaneity. The planet’s perspective shows the meeting point at 5 light-years, while the spaceship’s perspective indicates a shorter distance due to its motion. The solution tells us that both perspectives are valid within special relativity. But that leads to two possible ages for the universe. Those two possible ages question the validity of our measurements, and the validity of the current universe’s age, suggesting that the current framework may need refinement before a final result can be given.

Abstract: Core body temperature (CBT) is a fundamental physiological parameter tightly regulated by thermoregulatory mechanisms and is critically important for heat stress assessment, clinical management, and circadian rhythm research. Although invasive measurements such as pulmonary artery, esophageal, and rectal temperatures provide high accuracy, their practical use is limited by invasiveness, discomfort, and restricted feasibility for continuous monitoring in daily-life or field environments. Consequently, extensive efforts have been devoted to developing non-invasive CBT measurement and estimation techniques. This review provides an application-oriented synthesis of invasive reference methods and representative non-invasive approaches, including in-ear sensors, infrared thermography, ingestible telemetric sensors, heat-flux-based techniques, and model-based estimation using wearable physiological signals. For each approach, measurement principles, accuracy, invasiveness, usability, and application domains are comparatively examined, with particular emphasis on trade-offs between measurement fidelity and real-world implementability. Rather than ranking methods by absolute performance, this review highlights their relative positioning across clinical, occupational, and daily-life contexts. While no single non-invasive technique can universally replace invasive gold standards, recent advances in wearable sensing, heat-flux modeling, and multimodal estimation demonstrate growing potential for practical CBT monitoring. Overall, the findings suggest that future CBT assessment will increasingly rely on hybrid and context-aware systems that integrate complementary methods to enable reliable monitoring under real-world conditions.

Abstract: Rural defensive heritage sites are highly vulnerable assets that require decision-making under conditions of limited data and high uncertainty, particularly in the context of large-scale infrastructure projects and accelerating environmental processes. This study proposes a modular decision-support model for defining conservation priorities in a transparent, traceable, and data-sensitive manner, based on four selected fortress sites in the Yusufeli district of Artvin, Türkiye. The model employs a risk-based approach to quantify anthropogenic risks (AR) through the combined assessment of impact (I) and probability (P). Topographic and contextual vulnerability (TC) is structured through sub-indicators including visual dominance disruption, access discontinuities, landscape fragmentation, and microclimatic exposure, while material and intervention compatibility (MS) is evaluated as a distinct compatibility–risk component. These three modules are integrated through normalization and weighted aggregation into a single Priority Index (PI). In addition, the study introduces a Data Completeness Index (DCI) to explicitly address heterogeneity and gaps in field data, allowing prioritization outcomes to be interpreted with an associated confidence level. Laser-scanning-based documentation, deterioration mapping, and photographic records support the evidence-based construction of indicators. The proposed framework offers a transferable approach for generating intervention and monitoring priorities for rural defensive heritage under rapid landscape transformation, while explicitly managing data uncertainty rather than obscuring it.

Abstract: Obstructive sleep apnea (OSA) is a highly prevalent yet frequently underdiagnosed condition that is associated with significant cardiopulmonary, metabolic, and neurocognitive outcomes. Risk factors for OSA overlap with illnesses commonly observed in intensive care unit (ICU) patients, resulting in a disproportionately elevated burden in healthcare. This study evaluates the prevalence, diagnostic challenges, and management limitations of OSA in the ICU to identify strategies to improve awareness and outcomes in critically ill populations. An analysis of published literature was conducted using PubMed, EMBASE, and Scopus. Key search terms included “obstructive sleep apnea,” “ICU,” and “critical illness.” Results showed that OSA is present in up to 60–70% of ICU patients, yet only ~5% are formally diagnosed during hospitalization. Underdiagnosis is linked to prolonged mechanical ventilation, extubation failure as high as 30%, 2-fold higher perioperative complication rates, cardiovascular instability, 1.8-fold greater 30-day ICU readmission, and 2.2-fold mortality. Standard screening tools have limited applicability in ICU patients. Emerging alternatives, such as overnight oximetry, polygraphy, and machine learning models lack validation. Our analyses reveal that current diagnostic and treatment strategies are poorly adapted to critically ill patients. Integration of OSA as a part of ICU management, diagnosis, and intervention may reduce readmissions and mortality.

Abstract:

Background: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, motor hyperactivity and verbal and cognitive impulsivity. Impairments in executive functions (EFs), in particular working memory, monitoring and organization of daily life-are frequently observed in children diagnosed with ADHD, and are reflected in behavioural, social-emotional and learning difficulties. The development and use of technologies such as virtual reality (VR), augmented reality (AR) and mixed reality (MR) for ADHD have increased in recent years, using a variety of tools to support including PC, video games, wearable devices and tangible interfaces. Objectives: To systematically map the current state of research on the use of AR, VR and MR technologies to assess and/or enhance EFs in children with ADHD. To evaluate the effects on their quality of life and on families’ and caregivers’ burden reduction. To explore the interventions’ clinical validity. Methods: A scoping review according to PRISMA-ScR guidelines was conducted. A systematic search was carried out in the Scopus and Web of Science databases for studies published between 2015 and 2025.Empirical studies published in English that examined children with ADHD aged < 13 years were included. AR, VR, or MR-based interventions focused on EF were considered. For each study, the following features were recorded: year and country of publication, design, objectives, EFs considered, technology and hardware used, main results, and limitations. Results: Twenty studies were identified. The most frequently addressed functional domains were sustained and selective visual attention, working memory, and inhibition. Assessment interventions primarily involved the use of a head-mounted display (HMD) in conjunction with the Continuous Performance Test (CPT). Training interventions included immersive VR, serious video games, VR with motor or dual-task training, and MR. The results suggest that VR can enhance cognitive performance and sustained attention; however, longitudinal studies are required to evaluate its long-term effectiveness and integrate emotional skills. Conclusions: The use of these technologies is a promising strategy for assessment and training of EFs in children with ADHD. These tools provide positive, inclusive feedback and motivating tasks. Nevertheless, larger sample studies, longitudinal follow-ups to confirm the suitability and effectiveness of the technology-based programs are warranted.

Abstract: Background/Objectives: Axillary lymph node dissection (ALND) remains an essential component of breast cancer surgery for selected patients, particularly those with clinically involved nodes or residual disease after neoadjuvant therapy. However, ALND is consistently associated with postoperative lymphatic morbidity, including seroma formation, prolonged drainage, and breast cancer–related lymphedema (BCRL), which adversely affect quality of life and increase healthcare utilization. This review aims to evaluate contemporary ALND strategies with a particular focus on the Total Sealing Technique (TST), a technique-centered approach that emphasizes comprehensive lymphatic sealing rather than device substitution. Methods: A narrative review of the literature was conducted to synthesize available experimental, histopathological, and clinical evidence related to TST. Studies evaluating biological mechanisms, perioperative outcomes, long-term lymphatic complications, and health economic implications of TST were reviewed and contextualized alongside data from conventional electrocautery-based techniques and energy-device substitution strategies. Results: Across published studies, TST is consistently associated with reductions in postoperative drainage volume, duration of drain placement, incidence of seroma formation, and length of hospital stay. Importantly, long-term follow-up data demonstrate a marked reduction in the incidence of BCRL compared with conventional ALND techniques. These benefits are achieved without increases in operative time, perioperative complications, or compromise of oncological safety. From a health economic perspective, reductions in inpatient hospitalization, outpatient seroma management, and long-term lymphedema-related care translate into meaningful per-patient cost savings. Conclusions: The available evidence supports TST as a reproducible and scalable surgical strategy that effectively reduces both short-term postoperative morbidity and long-term lymphatic complications following ALND. By addressing lymphatic injury at the time of initial surgery, TST aligns with contemporary priorities in breast cancer care, including survivorship, quality of life, and value-based healthcare delivery.

Abstract: Direction-of-arrival (DOA) estimation is a fundamental problem in array signal processing with applications spanning radar, sonar, and wireless communications. Traditional subspace methods like MUSIC assume white Gaussian noise and often fail to exploit the noncircular property of many communication signals. This paper presents a tractable expectation-maximization (EM) algorithm that jointly estimates DOAs and the spatially colored noise covariance matrix while exploiting signal noncircularity through an extended observation model. We derive closed-form expressions for the E-step and M-step, establish convergence properties, and provide comprehensive performance analysis. Experimental results demonstrate that the proposed method achieves superior resolution and accuracy compared to conventional MUSIC and noncircular MUSIC, particularly in scenarios with strong spatial noise correlation. Monte Carlo simulations show RMSE improvements of up to 60% over standard methods at low SNR conditions. The algorithm successfully resolves sources separated by as little as 2 degrees with 100% detection rate, significantly outperforming existing techniques.

Abstract: Tourism destinations exposed to chronic natural hazards require robust analytical frameworks to understand and prioritize the factors that sustain post-disaster resilience. This study examines Baños de Agua Santa (Ecuador), a volcano-exposed destination whose long recovery trajectory illustrates the complexity of socioecological adaptation. Using a multidi-mensional FAHP model grounded in expert judgments, eight dimensions and fifty-six criteria were evaluated through fuzzy triangular numbers and the extended analysis method of Chang to capture uncertainty and ambiguity in decision-making. Results show a consistent and hierarchical structure of resilience, with experiential, economic-entrepreneurial, and sociocommunitarian dimensions emerging as the most influential drivers of post-disaster adaptability. Fifteen criteria—primarily perceptual, community-based, and endogenous—achieved “very high impact” status, including risk perception, basic education, individual resilience capacities, institutional coordination, and entrepreneurial environment. Conversely, limited healthcare infrastructure, low economic diversification, and national-level vulnerabilities were identified as critical weaknesses. The study concludes that post-disaster recovery in Baños is shaped by a bot-tom-up dynamic emphasizing agency, learning, and socioecological memory, and proposes an evidence-based Action Matrix for adaptive governance to guide prioritized, time-phased interventions. The FAHP model proves effective for transparent, context-sensitive prioritization in highly uncertain tourism environments.