Search Results (48)

Objectives: In this study, we aimed to evaluate the changes suggestive of maxillary anterior displacement in adults undergoing 3D-guided midpalatal piezocorticotomy-assisted Miniscrew-Assisted Rapid Palatal Expansion (MARPE), in addition to the contributing factors for forward maxillary movement and the subsequent immediate shift in the mandible. Methods: In this retrospective quasi-experimental study, cephalometric records of 80 adult patients (mean age 35.23 ± 8.76 years; 52 females and 28 males) were analyzed. Maxillary anterior displacement was assessed via SNA and A-Nperp(FH), while intermaxillary changes were measured using the ANB angle. Vertical and rotational changes were tracked through SN-MP, FH-MP, and various occlusal plane angles (OcP-FH, OcP-SN, OcP-GoMe). Facial height dimensions (TAFH, UAFH, LAFH, PFH) and dento-alveolar positions (U1-MP, U1LENGTH) were also recorded. Results: Following intervention, significant increases were observed in SNA (0.96°; 95% CI [0.48, 1.43]), ANB (1.42°; 95% CI [1.04, 1.80]), and A-Nperp(FH) (0.81 mm; 95% CI [0.24, 1.39]). The SN-GoMe angle increased by 0.98°, and Posterior Facial Height (PFH) decreased by 1.57 mm, while the upper incisor length (U1LENGTH) significantly decreased by 0.71 mm. Conclusions: In adults, 3D-guided midpalatal piezocorticotomy-assisted MARPE is associated with an increase in SNA, ANB, SN-GoMe, and A-Nperp(FH), and decreases in Posterior Facial Height (PFH) and the maxillary incisor length. The amount of mean midpalatal separation is moderately associated with the increase in SNA, while the increase in SNA is not associated with age or gender. Further 3D cephalometric studies would be beneficial to confirm the current findings. Full article

After the peak of the recent hype wave of interest surrounding the metaverse, virtual world applications remained in areas such as gaming, VR training, simulations, and collaboration. In this context, recordings are created which subsequently evolve into extensive collections that users may wish to access, search through, and retrieve items from. In order to facilitate searchability of metaverse recordings, it is necessary to adapt content analysis and indexing techniques to the specific characteristics of these recordings. This paper presents a reference model, the Processing Framework for Metaverse Recordings (PFMR), which details the phases of structural analysis, feature extraction, data mining, and feature fusion. The objective is to facilitate efficient retrieval of metaverse content. Our evaluation, based on a prototypical implementation, demonstrates the applicability and effectiveness of PFMR. This lays the groundwork for further integration of metaverse-specific content into Multimedia Information Retrieval systems. The evaluation of the 256 Metaverse Recording dataset shows that PFMRs’ domain-specific adaptability and integratability allows effective metaverse recording information retrieval for metaverse-specific features such as avatar detection, dialog mining, and toxicity classification. Full article

In our longitudinal study, we examined self-reported or explicit basic emotions, i.e., happiness, sadness, anxiety, and anger, in depressed patients during acute illness and inpatient treatment. For exploratory purposes, we also assessed implicit emotions. We analyzed how changes in emotional clarity relate to changes in emotions and depressive symptoms. A sample of depressed inpatients (n = 52) was examined at admission and on average after seven weeks of multimodal psychiatric treatment. A healthy control group (n = 52) was tested at the same time interval. Basic emotions were measured via the Differential Emotions Scale and a discrete-emotions variant of the Implicit Positive and Negative Affect Test. Emotional clarity was measured with the WEFG scales. Patients reported lower explicit happiness and heightened explicit sadness, anxiety, and anger compared to healthy controls, regardless of time of measurement. Across groups and time points, implicit happiness was greater than implicit sadness, anxiety, and anger, with no group differences. Patients’ emotional clarity improved and correlated with improvements in depressive symptoms, explicit happiness, sadness, and implicit anger. In summary, depressed patients experience heightened anxiety and anger, suggesting broader alterations of negative emotions beyond sadness. Increased emotional clarity during treatment was found to be correlated with changes in explicit and implicit affectivity. Full article

Background: Anterior open bite (AOB) is a complex malocclusion characterized by different vertical craniofacial growth and heterogeneous skeletal patterns, making objective diagnosis challenging using conventional cephalometric assessment alone. Recent advances in machine learning offer new opportunities to improve phenotypic characterization and diagnostic accuracy in orthodontics. Methods: This retrospective study analyzed lateral cephalometric records from 1056 orthodontic patients, comprising 621 patients with an anterior open bite and 435 healthy controls, all of whom were from the Arab population in Israel. Five clinically relevant cephalometric parameters related to vertical skeletal relationships were evaluated: the mandibular plane angle (ML-NSL), palatal plane angle (NL-NSL), posterior to anterior facial height ratio (PFH/AFH), gonial angle, and the facial axis. Statistical comparisons were made between the open bite and healthy subgroups, and these analyses were conducted in an exploratory framework to support hypothesis generation. A decision tree classifier was developed to distinguish AOB from healthy subjects using these features, and model performance was evaluated on a hold-out test set. Additionally, agglomerative hierarchical clustering was applied to explore latent craniofacial phenotypes. Results: Significant differences in vertical skeletal parameters were observed between open-bite and healthy subjects across various subgroups. The decision tree classifier achieved a test accuracy of 96.2%, with a precision, recall, and F1-score of approximately 0.97. ML-NSL emerged as the most influential feature, followed by facial axis and PFH/AFH. Unsupervised clustering identified ten distinct craniofacial clusters, including pure open bite and pure healthy phenotypes, as well as mixed clusters representing borderline or intermediate skeletal patterns. Clusters dominated by open bite cases exhibited steep mandibular planes, reduced PFH/AFH ratios, increased gonial angles, and decreased facial axis values, consistent with known vertical dysplasia patterns. Conclusions: Machine learning applied to cephalometric data enables accurate classification and meaningful phenotypic stratification of anterior open bite malocclusion. Beyond binary diagnosis, clustering analysis reveals clinically relevant subgroups that reflect varying degrees and types of vertical skeletal imbalance. These findings support the potential role of interpretable machine learning models as decision-support tools in orthodontic diagnosis and personalized treatment planning. Full article

Petrochemical fires pose severe threats to public safety and environmental sustainability, necessitating urgent advancements in efficient and eco-friendly fire suppression technologies. This study systematically investigated the influence of gas–liquid ratio (GLR) on the foam properties and fire suppression efficacy of a novel short-chain fluorocarbon (PFH-BZ) foam fire extinguishing agent. Through comprehensive experimental analysis, the underlying mechanism governing foam performance was elucidated, and the burn-back resistance of optimized formulation was evaluated. The results indicate that GLR significantly impacts PFH-BZ foam performance. Foaming capacity and structural stability exhibit a positive correlation with increasing GLR until reaching a plateau. Low GLRs result in insufficient foam formation and thermal stability, while inducing detrimental combustion intensification. Conversely, excessively high GLRs impair foam spreading capacity, hindering rapid extinguishment. The optimal fire extinguishing performance is achieved at a GLR of 12, where PFH-BZ foam attains an excellent balance among drainage characteristics, spreading capacity, and structural stability. This optimized formulation achieves complete extinguishment within 26.16 s and maintains burn-back resistance of 662.37 s while effectively mitigating the vapor explosion phenomenon. These findings provide critical guidance for the application of a PFH-BZ-based foam extinguishing agent and deepen understanding of the influence of system parameters on suppression performance. Full article

To enhance the efficiency and accuracy of partial-to-whole point cloud registration for complex workpieces, this paper presents a novel method based on the Mean Feature Descriptor (MFD). The proposed approach extracts geometric features from key points in the scanned point cloud, constructs local feature descriptors using a localized coordinate system, and performs coarse registration. Compared to conventional local descriptor-based methods, the MFD algorithm not only effectively captures local geometric characteristics but also significantly improves computational efficiency while maintaining high registration accuracy. Experimental results demonstrate that the MFD-based method substantially accelerates registration and measurement processes for complex workpieces. It exhibits strong robustness against noise and varying point cloud resolutions, outperforming existing descriptors such as PFH, FPFH, and HoPPF in terms of F1 score and matching precision. The method achieves reliable registration even under challenging conditions, such as partial overlap and geometric feature sparsity. Notably, the MFD descriptor inherently captures geometric symmetry-invariant features of local point cloud regions especially symmetric interfaces of complex workpieces. This ensures stable registration performance even when partial scans only preserve part of the workpiece’s symmetric structure. Full article

Addressing the environmental challenges posed by traditional foam extinguishing agents containing persistent pollutants, the development of eco-friendly alternatives has become imperative. This study investigates the effect of xanthan gum (XG) on the fire extinguishing performance of PFH-BZ foam formulated with short-chain fluorocarbon surfactant. By analyzing foam formation, drainage characteristics, and suppression process, the underlying mechanism by which XG influences foam extinguishing performance was elucidated. The results indicate that XG exerts dual effects on foam properties. While its viscosity-increasing effect improves foam stability, excessive XG addition impairs foaming and spreading capabilities, reducing fuel surface coverage and smothering efficiency. Moreover, a high concentration of XG hinders drainage behavior, which in turn inhibits the formation of spreadable aqueous films, thereby reducing cooling and extinguishing efficiency. The PFH-BZ foam with 0.02 wt.% XG exhibits excellent foaming and spreading capabilities, enabling rapid coverage of fuel surfaces. Additionally, its moderate drainage characteristics facilitate spreadable aqueous film formation, achieving efficient cooling and smothering effects. The optimized PFH-BZ foam exhibits the shortest extinction time of 35.4 s, the lowest transient temperature rise of 60.8 °C, and the highest cooling rate of 16.8 °C/s. Environmental assessments reveal that the optimized PFH-BZ foam exhibits higher biodegradability than conventional foam. Full article

Metaverse Recordings (MVRs), screen recordings of user experiences in virtual environments, represent a mostly underexplored field. This article addresses the integration of MVR and Multimedia Information Retrieval (MMIR). Unlike conventional media, MVRs can include additional streams of structured data, such as Scene Raw Data (SRD) and Peripheral Data (PD), which capture graphical rendering states and user interactions. We explore the technical facets of recordings in the Metaverse, detailing diverse methodologies and their implications for MVR-specific Multimedia Information Retrieval. Our discussion not only highlights the unique opportunities of MVR content analysis, but also examines the challenges they pose to conventional MMIR paradigms. It addresses the key challenges around the semantic gap in existing content analysis tools when applied to MVRs and the high computational cost and limited recall of video-based feature extraction. We present a model for MVR structure, a prototype recording system, and an evaluation framework to assess retrieval performance. We collected a set of 111 MVRs to study and evaluate the intricacies. Our findings show that SRD and PD provide significant, low-cost contributions to retrieval accuracy and scalability, and support the case for integrating structured interaction data into future MMIR architectures. Full article

Objectives: Previous literature has already discussed the effects of age and sex on the diagnosis and treatment of malocclusion problems. However, this effect varies among different ethnic groups. These differences have not yet been investigated in many populations, such as Arab orthodontic patients and residents of Israel. Therefore, it is crucial to understand such variations in specific populations for better diagnosis and treatment. The main aim of this study is to provide novel knowledge concerning skeletal classes I and II among a cohort of Arab patients who are citizens of Israel. We used parameters obtained from lateral cephalograms to understand the variations among different sex and age subgroups. We also examined the correlations and performed principal component analysis (PCA). Methods: This study was based on the coded records of 394 Arab patients diagnosed with skeletal Class I occlusion (SCIO) or skeletal Class II malocclusion (SCIIMO), according to the individualized ANB (Calculated_ANB) of Panagiotidis and Witt. Results: Among patients with SCIO, males had a significantly more horizontal growth pattern (PFH/AFH) and anterior mandible rotation (ML-NSL) than females. Regarding patients with SCIIMO, female adults had more hyperdivergent jaw bases than adolescents (ML-NL) and a more posteriorly rotated mandible (ML-NSL). Spearman’s analysis revealed many significant correlations, like Calculated_ANB, ANB angle, and Wits appraisal. The PCA results showed a remarkable ability to explain 88.6% of the sample variance using four principal components. Conclusions: This research revealed new information regarding Arab orthodontic patients diagnosed with skeletal class I or II. The results demonstrate the differences between the two classes. In addition, this study demonstrated the variation and correlation of cephalometric parameters among different sex and age subgroups in skeletal class I and II Arab patients, especially considering Calculated_ANB. Therefore, this study highlights the need to consider these differences when diagnosing patients and to distinguish the differences across different sex and age subgroups in the diagnosis and treatment process. Furthermore, the PCA results showed the importance of ML-NSL, SN-Pg, PFH/AFH ratio, and NL-ML in explaining the data variance. Full article

The application of soil organic amendments is a well-established approach to enhancing soil fertility; yet the effects of poultry feather hydrolysate (PFH) on temperate coarse-textured agricultural soils remain underexplored. A six-month microcosm experiment was conducted to determine the effects of PFH in different states (liquid or solid) and addition rates (none, low, or high; i.e., 0, 4, or 8 t dw ha⁻¹, respectively) on microbial activity, nutrient availability and retention, and organic matter (OM) stabilization in two coarse-textured soils (loamy sand or sandy loam). Sandy loam soil exhibited a stronger response to PFH application, supporting 20% higher microbial activity, 35% higher nutrient retention, and 89% higher OM content in soil aggregates compared to loamy sand soil, reflecting enhanced OM stabilization. Moreover, PFH in the liquid state demonstrated more prolonged microbial activity and more sustained release of nutrients compared to the solid state. Finally, at the end of incubation, the high addition rate of PFH significantly increased soil nutrient content by 106%, while the low addition rate limited the increase to 39%, both compared to the no addition rate. Overall, the results suggest that PFH, particularly in the liquid state and at the high addition rate, serves as an effective soil organic amendment, enhancing microbial activity and soil fertility while emphasizing the importance of soil texture in optimizing its application. Full article

Retrieval-Augmented Generation (RAG) has become a central approach to enhance the factual consistency and domain specificity of large language models (LLMs) by incorporating external context at inference time. However, most existing RAG systems rely on dense vector-based similarity, which fails to capture complex semantic structures, relational dependencies, and multimodal content. In this paper, we introduce Graph Codes—a matrix-based encoding of Multimedia Feature Graphs—as an alternative retrieval paradigm. Graph Codes preserve semantic topology by explicitly encoding entities and their typed relationships from multimodal documents, enabling structure-aware and interpretable retrieval. We evaluate our system in two domains: multimodal scene understanding (200 annotated image-question pairs) and clinical question answering (150 real-world medical queries with 10,000 structured knowledge snippets). Results show that our method outperforms dense retrieval baselines in precision (+9–15%), reduces hallucination rates by over 30%, and yields higher expert-rated answer quality. Theoretically, this work demonstrates that symbolic similarity over typed semantic graphs provides a more faithful alignment mechanism than latent embeddings. Practically, it enables interpretable, modality-agnostic retrieval pipelines deployable in high-stakes domains such as medicine or law. We conclude that Graph Code-based RAG bridges the gap between structured knowledge representation and neural generation, offering a robust and explainable alternative to existing approaches. Full article

Background and Objectives: Extracorporeal membrane oxygenation (ECMO) can support patients with severe cardiopulmonary failure, but it poses risks such as hemolysis, leading to complications. Plasma-free hemoglobin (PFH) is a hemolysis biomarker, with elevated levels linked to mortality. This study evaluates PFH and ECMO survival in COVID-19, non-COVID-19 pulmonary, and cardiac patients, focusing on late PFH spikes. Materials and Methods: We retrospectively analyzed 122 ECMO patients treated at our tertiary hospital (January 2020–December 2021). Patients were categorized by indication: post-COVID-19, non-COVID-19 pulmonary, or cardiac. We classified patients as Expired (died during ECMO or ≤30 days post-ECMO) or Survived (>30 days post-ECMO). Data included demographics, ECMO duration, and PFH values at 24 h and during the last 3 and 5 ECMO days. Groups were compared using two-tailed t-tests, with p < 0.05 indicating significance. Results: COVID-19 patients survived after significantly longer ECMO duration than non-COVID-19 pulmonary and cardiac patients. Expired COVID-19 patients had higher PFH values during the last 3 and 5 days of ECMO compared to survivors. Cardiac patients had the highest overall PFH levels regardless of mortality. No significant differences in PFH trends were observed between non-COVID-19 pulmonary and cardiac patients. Conclusions: Late PFH spikes correlated with mortality in COVID-19 patients, suggesting the utility of measuring late PFH spikes in ECMO management. Additionally, COVID-19 pulmonary patients survived when undergoing ECMO significantly longer than both groups, while VA ECMO was more prone to hemolysis. However, technical cannulation differences and frequent use of an Impella pump in cardiac patients may increase blood stress and PFH values. Full article

The recording of metaverse experiences supports various use cases in collaboration, VR training, and more. Such Metaverse Recordings can be created as multimedia and time series data during the 3D rendering process of the audio–video stream for the user. To search in a collection of recordings, Multimedia Information Retrieval methods can be used. Also, querying and accessing Metaverse Recordings based on the recorded time series data is possible. The presentation of human-perceivable results of time-series-based Metaverse Recordings is a challenge. This paper demonstrates an approach to generating human-perceivable media from time-series-based Metaverse Recordings with the help of generative artificial intelligence. Our findings show the general feasibility of the approach and outline the current limitations and remaining challenges. Full article

Background/Objectives: Ptosis surgery corrects drooping upper eyelids, improving function and esthetics. Traditional methods like marginal reflex distance (MRD) and palpebral fissure height (PFH) offer limited one-dimensional measurements. This study evaluates AI-based corneal exposure ratio (CER) analysis, a two-dimensional approach, compared to manual ImageJ methods for assessing ptosis surgery outcomes. Methods: In this prospective study, 100 eyes from 50 patients were analyzed using both methods. AI-based CER measurements were compared to manual ImageJ measurements for reliability and accuracy. Results: AI-based CER measurements were comparable to manual ImageJ, with high reliability (ICC 0.992, 0.985). Preoperative CER was 55.34% (manual) and 55.79% (AI), increasing to 75.92% (manual) and 75.84% (AI) postoperatively. The AI tool showed minimal bias and high repeatability (ICC 1.000), offering faster automated measurements. Conclusions: AI-based CER analysis matched manual methods in accuracy but provided significant efficiency advantages, making it suitable for clinical use. Limitations include a small homogeneous sample size and reliance on 2D imaging, which may not fully capture three-dimensional changes. Further studies are recommended to enhance generalizability and precision. Full article

Hypoxia, a phenomenon that occurs when the oxygen level in tissues is lower than average, is commonly observed in human solid tumors. For oncological treatment, the hypoxic environment often results in radioresistance and chemoresistance. In this study, a new multifunctional oxygen carrier, carboxymethyl hexanoyl chitosan (CHC) nanodroplets decorated with perfluorohexane (PFH) and superparamagnetic iron oxide (SPIO) nanodroplets (SPIO@PFH-CHC), was developed and investigated. PFH-based oxygen carriers can augment oxygenation within tumor tissues, thereby mitigating radioresistance. Concurrently, oxygenation can cause deoxyribonucleic acid (DNA) damage via oxygen fixation and consequently suppress cancer cell proliferation. Moreover, these pH-sensitive nanodroplets allow higher cellular uptake with minimal cytotoxicity. Two distinctive mechanisms of SPIO@PFH-CHC nanodroplets were found in this study. The SPIO nanoparticles of the SPIO@PFH-CHC nanodroplets can generate hydroxyl radicals (HO^•) and other reactive oxygen species (ROS), which is vital to chemodynamic therapy (CDT) via the Fenton reaction. Meanwhile, the higher X-ray absorption among these nanodroplets leads to a local energy surge and causes more extensive deoxyribonucleic acid (DNA) damage via oxygen fixation. This study demonstrates that low cytotoxic SPIO@PFH-CHC nanodroplets can be an efficient radiosensitizer for radiation therapy. Full article