Search Results (8,539)

Background/Objectives: Human leukocyte antigen B27 (HLA-B27) is a genetic marker strongly associated with various inflammatory rheumatic diseases, particularly those within the spondyloarthritis spectrum. Its presence influences disease onset, clinical severity, and therapeutic strategies. However, comparative data between HLA-B*27-positive and -negative patients, especially in Eastern European populations, remain limited. The study aimed to investigate the clinical, paraclinical, and psychosocial differences between HLA-B*27-positive and -negative individuals diagnosed with rheumatic diseases, in order to better understand the implications of HLA-B27 status on disease expression and patient quality of life. Methods: A cross-sectional, observational study was conducted between June 2023 and December 2024 at the Emergency Clinical Hospital for Children “Sf Ioan” in Galati, Romania, in collaboration with “Dunarea de Jos” University. Fifty adult patients with various rheumatic conditions were enrolled and stratified into HLA-B*27-positive (n = 22) and -negative (n = 28) groups. Data collection included clinical evaluations, laboratory biomarkers (CRP = C-reactive protein; ESR = erythrocyte sedimentation rate), and a structured quality-of-life questionnaire. Statistical analysis was performed using SPSS v27. Results: HLA-B*27-positive patients were significantly younger (mean age 46.00 vs. 55.07 years, p = 0.018) and had higher CRP levels (>1 mg/dL in 53.33% vs. 0%, p = 0.001). Ankylosing spondylitis was more prevalent in this group (22.73% vs. 3.57%, p = 0.039). Magnetic resonance imaging (MRI) was more frequently used (68.18% vs. 39.29%, p = 0.042), indicating greater suspicion of axial involvement. HLA-B27-positive patients also reported higher perceived stress (mean score 2.41 vs. 1.21, p< 0.001). Conclusions: HLA-B*27 positivity is associated with earlier disease onset, increased systemic inflammation, greater axial involvement, and higher psychological stress. These findings emphasise the need for personalised, multidisciplinary care that integrates both medical and psychological support for HLA-B*27-positive patients. Full article

This paper proposes a novel heart rate detection scheme to address key challenges in millimeter-wave radar-based vital sign monitoring, including weak signals, various types of interference, and the demand for high-precision and super-resolution frequency estimation under practical computational constraints. First, we propose a multi-dimensional coherent accumulation (MDCA) method to enhance the signal-to-noise ratio (SNR) by fully utilizing both spatial information from multiple receiving channels and temporal information from adjacent range bins. Additionally, we are the first to apply the fast iterative interpolated beamforming (FIIB) algorithm to radar-based heart rate detection, enabling super-resolution frequency estimation with low computational complexity. Compared to the traditional fast Fourier transform (FFT) method, the FIIB achieves an improvement of 1.08 beats per minute (bpm). A reordering strategy is also introduced to mitigate potential misjudgments by FIIB. Key parameters of FIIB, including the number of frequency components L and the number of iterations Q, are analyzed and recommended. Dozens of subjects were recruited for experiments, and the root mean square error (RMSE) of heart rate estimation was less than 1.12 bpm on average at a distance of 1 meter. Extensive experiments validate the high accuracy and robust performance of the proposed framework in heart rate estimation. Full article

This study delves into the response characteristics of core grounding current signals in power transformers across different operating conditions, aiming to enhance the accuracy of transformer condition assessment. Existing detection technologies often rely on single-parameter methods, which fall short in providing a comprehensive evaluation of transformer conditions. To address this limitation, this research develops a wideband circuit model based on multi-conductor transmission line theory and backed by experimental validation. The model systematically investigates the response mechanisms of core grounding current to various electrical stresses, including impulse voltages, power-frequency harmonics, and partial discharges. The findings reveal distinct response characteristics of core grounding current under different stresses. Under impulse voltage excitation, the core current exhibits high-frequency oscillatory decay with characteristics linked to voltage waveform parameters. In harmonic conditions, the current spectrum shows linear correspondence with excitation voltages, with no resonance below 1 kHz. Partial discharges induce high-frequency oscillations in the grounding current due to multi-resonant networks formed by distributed winding-core parameters. This study establishes a new theoretical framework for transformer condition assessment based on core grounding current analysis, offering critical insights for optimizing detection technologies and overcoming the limitations of traditional methods. Full article

γ-TiAl alloy is a lightweight high-temperature structural material, featuring low density, excellent high-temperature strength, creep resistance, etc. It is a key material in the aerospace field. However, the essential defects of γ-TiAl alloys, such as poor room-temperature plasticity and low fracture toughness, have become the biggest obstacles to their practical application. Therefore, in this paper, the physical mechanism of modification of the mechanical properties and electronic structure of γ-TiAl alloys by doping with Sc, V, and Si was investigated by using the first-principles pseudopotential plane wave method. This paper specifically calculates the geometric structure, phonon spectrum, mechanical properties, electron density of states, Mulliken population analysis, and differential charge density of γ-TiAl alloys before and after doping. The results show that after doping, the structural parameters of γ-TiAl have changed significantly, and the doping models all have thermodynamic stability. The B, G, and E values of the doped system are, respectively, within the range of 94–112, 57–69, and 143–170 GPa, indicating that the material’s ability to resist compressive deformation is weakened. Moreover, the B/G values change from 1.5287 to 1.6350, 1.7279, and 1.6327, respectively, and a transformation from brittleness to plasticity occurs. However, it is still lower than the critical value of 1.75, indicating that the doped γ-TiAl alloy material retains its high-strength characteristics while also exhibiting a certain degree of toughness. The total elastic anisotropy index of the doped system increases, and the degree of anisotropy of mechanical behavior significantly increases. The total electron density of states diagram indicates that γ-TiAl alloys possess conductive properties. The covalent interactions between doped atoms and adjacent atoms have been weakened to varying degrees, which is manifested as a significant change in the charge distribution around each atom. The above results indicate that the doping of Sc, V, and Si can effectively tune the mechanical properties and electronic structure of γ-TiAl alloys. Full article

Drug-coated balloons (DCBs) have transformed percutaneous coronary intervention (PCI) by delivering antiproliferative drugs directly to the arterial wall, offering a stent-less approach that mitigates the risks associated with permanent metallic implants. Initially developed for in-stent restenosis (ISR), DCBs have demonstrated robust efficacy in reducing neointimal hyperplasia and target lesion revascularization (TLR) rates across diverse coronary lesions, including small vessel disease (SVD), de novo lesions, and complex anatomies such as bifurcation lesions. Paclitaxel-coated balloons have long been the cornerstone of DCB therapy due to their established clinical outcomes, but sirolimus-coated balloons are emerging as a promising alternative with potentially superior safety profiles and sustained drug release. The pharmacological mechanism of DCBs relies on rapid drug transfer during brief balloon inflation, achieving high local concentrations without residual foreign material. Landmark trials, such as BASKET-SMALL 2, RESTORE SVD, and AGENT IDE, have demonstrated comparable or non-inferior outcomes of DCBs versus drug-eluting stents (DESs) in specific settings, with lower rates of stent thrombosis and shorter dual antiplatelet therapy (DAPT) requirements. Despite these advances, challenges persist, including optimizing drug formulations, ensuring uniform delivery, and addressing calcified lesions. Ongoing research into novel coatings, dual–drug systems, and artificial intelligence (AI)-guided interventions is poised to redefine PCI strategies. This review provides a comprehensive analysis of drug-coated balloon (DCB) angioplasty, not limited to specific clinical scenarios such as in-stent restenosis, small vessel disease, or bifurcation lesions, highlighting their transformative role in coronary artery disease (CAD) management. Instead, it addresses the full spectrum of pharmacological principles, mechanisms of action, clinical indications, comparative efficacy across various coronary artery disease contexts, and future directions of DCBs. Full article

We investigate the electronic properties of atomic chains placed on group-14 two-dimensional materials, Xenes, by analyzing the local electronic properties. Our results show that the hybridization between the chain and the substrate leads to significant modifications in the local density of states at each chain site, including peak splitting, broadening, and asymmetry. These effects are particularly pronounced for plumbene. Owing to the substrate’s V-shaped-like density of states, the chains exhibit strong localization effects and significant intensity variations in the electronic energy spectrum. In addition the present analysis reveals the emergence of charge density waves in atomic chains, for which the appearance and stability conditions are identified and provided. The charge density waves are more pronounced and stabilized by a specific electronic spectrum of Xenes, allowing them to penetrate deeper into the chain interior. Our findings contribute to the broader understanding of the interaction between one-dimensional chains and two-dimensional Xene materials, which have significant implications for developing advanced hybrid nanostructures and next generation electronic devices. Full article

Accurate detection of water in organic solvents is essential for various industrial and analytical applications. In this study, we present a simple, rapid, and sensitive fluorescence-based method for water quantification using 1,5-diaminonaphthalene (1,5-DAN) as a solvatochromic probe. This method exploits the excited-state intramolecular charge transfer (ICT) behavior of 1,5-DAN, which undergoes a symmetry-breaking transition in the presence of protic solvents such as water, leading to a distinct redshift in its emission spectrum and a change from a structured double-band to a single ICT band. We demonstrate that, in solvents like acetonitrile and tetrahydrofuran, the emission maxima of 1,5-DAN correlate linearly with water content up to 100%, while ratiometric analysis of peak intensities allows for sensitive detection in low concentration ranges. This method achieved limits of detection as low as 0.08% (v/v) in MeCN, with high reproducibility and minimal sample preparation. Application to a real MeCN–water azeotrope confirms the method’s accuracy, matching classical refractometric measurements. Our findings highlight the potential of 1,5-DAN as a low-cost, efficient, and non-destructive fluorescent sensor for monitoring moisture in organic solvents, offering a practical alternative to conventional methods such as Karl Fischer titration for both bulk and trace water analysis. Full article

Spectral reflectance of plants can be readily associated with physiological and biochemical parameters. Thus, relating spectral data to amino acid contents in different genetic materials provides an innovative and efficient approach for understanding and managing genetic diversity. Therefore, this study had two objectives: (I) to differentiate genetic materials according to amino acid contents and spectral reflectance; (II) to establish the relationship between amino acids and spectral bands derived from hyperspectral data. The research was conducted with 32 soybean genetic materials grown in the field during the 2023–2024 crop year. The experimental design involved randomized blocks with four replicates. Leaf spectral data were collected 60 days after plant emergence, when the plants were in full bloom. Three leaf samples were collected from the third fully developed trifoliate leaf, counted from top to bottom, from each plot. The samples were taken to the laboratory, where reflectance readings were obtained using a spectroradiometer, which can measure the 350–2500 nm spectrum. Wavelengths were grouped as means of representative intervals and then organized into 28 bands. Subsequently, the leaf samples from each plot were subjected to quantification analyses for 17 amino acids. Then, the soybean genotypes were subjected to a PCA–K-means analysis to separate the genotypes according to their amino acid content and spectral behavior. A correlation network was constructed to investigate the relationships between the spectral variables and between the amino acids within each group. The groups formed by the different genetic materials exhibited distinct profiles in both amino acid composition and spectral behavior. Leaf reflectance data proved to be efficient in identifying differences between soybean genotypes regarding the amino acid content in the leaves. Leaf reflectance was effective in distinguishing soybean genotypes according to leaf amino acid content. Specific and high-magnitude associations were found between spectral bands and amino acids. Our findings reveal that spectral reflectance can serve as a reliable, non-destructive indicator of amino acid composition in soybean leaves, supporting advanced phenotyping and selection in breeding programs. Full article

The therapeutic potential of cannabinoids and other ligands of cannabinoid receptors attracts considerable attention due to their diverse pharmacological effects and utility in various medical applications. However, challenges such as low solubility, limited bioavailability, and potential side effects hinder their broad clinical use. Nanoformulation techniques offer a promising approach to address these issues and optimize the therapeutic effectiveness of cannabinoids and other cannabinoid receptor ligands. This comprehensive review explores the advancements in nanoformulation strategies to enhance the therapeutic efficacy and safety of synthetic cannabinoids and related compounds, such as CB13, rimonabant, and HU-211, which have been studied in a range of preclinical models addressing conditions such as neuropathic pain, depression, and cancer. The review discusses various nanocarriers employed in this field, including lipid-based, polymeric, and hybrid nanoparticles, micelles, emulsions, and other nanoengineered carriers. In addition to formulation approaches, this review provides an in-depth analysis of chemical structures and their effect on compound activity, especially in the context of the affinity for the cannabinoid type 1 receptor in the brain, which is chiefly responsible for the psychoactive effects. The provided summary of research concerning either chemical modifications of existing cannabinoids or the creation of new compounds that interact with cannabinoid receptors, followed by the development of nanoformulations for these agents, allows for the identification of new research directions and future perspectives for Cannabis-based medicine. In conclusion, the combination of nanotechnology and cannabinoid pharmacology holds promise for delivering more effective and safer therapeutic solutions for a broad spectrum of medical conditions, making this an exciting area of research with profound implications for the healthcare and pharmaceutical industries. Full article

Efficient and convenient intelligent online detection methods can provide important technical support for the standardization of processing flow in the tea industry. Hence, this study focuses on the key chemical indicators—tea pigments in the rolling process of black tea as the research object, and uses multi-source information fusion methods to predict the changes of tea pigments content. Firstly, the tea pigments content of the samples under different rolling time series of black tea is determined by system analysis methods. Secondly, the spectra and images of the corresponding samples under different rolling time series are simultaneously obtained through the portable near-infrared spectrometer and the machine vision system. Then, by extracting the principal components of the image feature information and screening characteristic wavelengths from the spectral information, low-level and middle-level data fusion strategies are chosen to effectively integrate sensor data from different sources. At last, the linear (PLSR) and nonlinear (SVR and LSSVR) models are established respectively based on the different characteristic data information. The research results show that the LSSVR based on middle-level data fusion strategy have the best effect. In the prediction results of theaflavins, thearubigins, and theabrownins, the correlation coefficients of the testing sets are all greater than 0.98, and the relative percentage deviations are all greater than 5. The complementary fusion of the spectrum and image information effectively compensates for the problems of information redundancy and feature missing in the quantitative analysis of tea pigments content using the single-modal data information. Full article

Metal hydrides are emerging hydrogen-storage materials that have attracted much attention for their stability and practicality. The novel magnesium-based metal hydride Mg₂CsH₉ was investigated using the CALYPSO software (version 7.0). First-principles predictive methods were then employed to investigate the structural, mechanical, electronic, optical, and hydrogen-storage properties of Mg₂CsH₉ and its alkali metal substitution structure Mg₂RbH₉. The negative formation energy, compliance with the Born stability criterion, and absence of imaginary modes in the phonon spectrum collectively confirm the thermodynamic, mechanical, and dynamic stability of Mg₂XH₉ (X = Cs, Rb), fulfilling the basic criteria for practical hydrogen-storage applications. Mg₂RbH₉ is particularly outstanding in terms of its hydrogen-storage capacity, with a gravimetric capacity of 6.34 wt% and a volumetric capacity as high as 92.70 g H₂/L, surpassing many conventional materials. The pronounced anisotropic characteristics of both compounds further enhance their practicality and adaptability to complex working conditions. An analysis of Poisson’s ratio revealed that the chemical bonding in both compounds is predominantly ionic. The details of the band structures and density of states indicate that Mg₂CsH₉ and Mg₂RbH₉ are semiconductors. Their optical properties confirm them as being high-refractive-index materials. Full article

The construction industry, a cornerstone of global economic growth, continues to struggle with entrenched inefficiencies, including low productivity, cost overruns, and fragmented project delivery. Addressing these persistent challenges requires more than incremental improvements, it demands a strategic unification of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. This systematic review synthesizes evidence from 64 academic studies to identify the most influential tools, techniques, and methodologies across these domains, revealing both their individual strengths and untapped synergies. The analysis highlights widely adopted Lean practices such as the Last Planner System (LPS) and Just-In-Time (JIT); BIM capabilities across 3D, 4D, 5D, 6D, and 7D dimensions; and a spectrum of digital innovations including Digital Twins, AR/VR/MR, AI, IoT, robotics, and blockchain. Crucially, the review demonstrates that despite rapid advancements, integration remains sporadic and unstructured, representing a critical research and industry gap. By moving beyond descriptive mapping, this study establishes an essential foundation for the development of robust, adaptable integration frameworks capable of bridging theory and practice. Such frameworks are urgently needed to optimize efficiency, enhance sustainability, and enable innovation in large-scale and complex construction projects, positioning this work as both a scholarly contribution and a practical roadmap for future research and implementation. Full article

Background/Objectives: Autism Spectrum Disorder (ASD) includes significant feeding difficulties, behavioral issues, and communication deficits that are linked to serious medical complications and developmental challenges. The Brief Autism Mealtime Behavior Inventory (BAMBI) is a commonly used tool to screen for mealtime behavior problems in children with ASD; however, it lacks validation for use within the Greek-Cypriot population. The current study sought to present the translation, cultural adaptation, and validation of the BAMBI for Greek-Cypriot parents of children with ASD. Methods: Three bilingual experts translated the inventory into Greek, following the translation guidelines by the World Health Organization. The inventory was then administered to 117 parents: 42 children with ASD and 75 typically developing children. Principal Component Analysis was used to obtain the tool’s statistical reliability and validity. Results: BAMBI-Gr demonstrated strong internal consistency, as indicated by a Cronbach’s alpha of 0.755, and showed excellent test–retest reliability, with an intraclass correlation coefficient of 0.999. PCA identified three key factors: General Refusals, Refusing Food, and Autism-Related Features. Significant differences in BAMBI-Gr scores of the comparative group of parents of children with ASD and parents of typically developing children highlighted the tool’s sensitivity in detecting mealtime behavior problems. Receiver Operating Characteristics analysis set the cut-off points for optimum distinguishing of feeding problems at 46.00 (sensitivity 0.738, 1-specificity 0.000). Conclusions: The Greek-translated version of the BAMBI demonstrates validity and effectiveness as a parent-reported assessment tool for identifying feeding and mealtime difficulties in children with ASD. Full article

This perspective paper proposes a theoretical framework for investigating potential associations between Long COVID and rising autism spectrum disorder (ASD) prevalence through established epidemiological methodologies. I propose examining temporal correlations, biological mechanisms, and rigorous methodological approaches, including Mendelian randomization, animal models, and evidence-based analyses, that could distinguish association from causation. The proposed framework recognizes autism as neurodiversity while suggesting investigation of environmental factors that may influence expression of genetic predispositions. Hypothesized key mechanisms include neuroinflammation, cytokine alterations, and immune dysfunction. I emphasize the critical distinction between demonstrating statistical associations and establishing causal influence, proposing specific experimental designs that could test causality. This paper presents conceptual frameworks requiring future empirical validation and does not include original data analysis. Full article

Background/Objectives: Positive psychology interventions (PPIs) may enhance well-being in individuals with severe psychiatric conditions (SPCs), yet little is known about individual differences in treatment response. Methods: We conducted a secondary analysis of a single-blind, parallel-group randomized controlled trial. A total of 119 adults receiving outpatient mental health care were randomized to an 11-week multicomponent PPI plus treatment as usual (PPI + TAU) or TAU alone. A priori demographic and baseline clinical variables (e.g., age, gender, education, diagnosis, symptom severity) were tested as predictors and moderators of six well-being outcomes. Moderation analyses were conducted using the PROCESS macro (version 4.1) for SPSS version 29.0, with simple slopes explored for significant interactions. Analyses followed an intention-to-treat approach. Results: Individuals who were unemployed, had a diagnosis within the psychosis spectrum, or exhibited high interpersonal sensitivity showed improvements in well-being irrespective of the treatment modality received. Older patients, those attending more weekly therapy sessions, and individuals with less somatization, hostility, or life satisfaction levels responded particularly well to the specialized PPI + TAU treatment. While several interactions were significant at p < 0.01, none remained significant after Bonferroni–Holm correction. Nevertheless, the patterns were consistent and theoretically grounded. Conclusions: Individual characteristics may influence the effectiveness of PPIs in SPC populations. Identifying predictors and moderators can inform more personalized interventions. The findings warrant replication. Trial registration: ClinicalTrials.gov, NCT01436331. Full article