Search Results (628)

Background: Post-traumatic trigeminal neuropathic pain (PTTNP) is a chronic condition often caused by dental procedures such as implant placement or tooth extraction. It involves persistent pain and sensory disturbances, negatively affecting the quality of life of patients. Methods: This retrospective observational study was conducted at Chosun University Dental Hospital and included 120 patients diagnosed with PTTNP involving the orofacial region. Patient data were collected between January 2014 and December 2023. Among them, 79 patients (65.8%) developed PTTNP following dental implant placement, with a total of 121 implants analyzed. The inferior alveolar nerve was most frequently involved. Clinical factors, including the time to treatment, removal of the causative factor, the Sunderland injury grade, and the type of treatment, were evaluated. Pain intensity and sensory changes were assessed using the visual analog scale (VAS). Results: Treatment initiated within the early post-injury period, commonly regarded as within three months, and implant removal tended to improve outcomes. Pharmacological therapy was the most commonly employed modality, particularly gabapentinoids (e.g., gabapentin, pregabalin) and tricyclic antidepressants such as amitriptyline. However, combined therapy, which included pharmacologic, physical, and surgical approaches, was associated with the greatest sensory improvement. Conclusions: Prompt, multidisciplinary intervention may enhance recovery in patients with PTTNP. Implant-related injuries require careful management, and multimodal strategies appear more effective than monotherapies. Full article

This paper presents a UAV-based building crack real-time detection system that integrates an improved YOLOv8 algorithm with Linear Active Disturbance Rejection Control (LADRC). The system is equipped with a high-resolution camera and sensors to capture high-definition images and height information. First, a trajectory tracking controller based on LADRC was designed for the UAV, which uses a linear extended state observer to estimate and compensate for unknown disturbances such as wind interference, significantly enhancing the flight stability of the UAV in complex environments and ensuring stable crack image acquisition. Secondly, we integrated Convolutional Block Attention Module (CBAM) into the YOLOv8 model, dynamically enhancing crack feature extraction through both channel and spatial attention mechanisms, thereby improving recognition robustness in complex backgrounds. Lastly, a skeleton extraction algorithm was applied for the secondary processing of the segmented cracks, enabling precise calculations of crack length and average width and outputting the results to a user interface for visualization. The experimental results demonstrate that the system successfully identifies and extracts crack regions, accurately calculates crack dimensions, and enables real-time monitoring through high-speed data transmission to the ground station. Compared to traditional manual inspection methods, the system significantly improves detection efficiency while maintaining high accuracy and reliability. Full article

Background: Inhaled corticosteroids (ICSs) are a cornerstone in asthma management, particularly during exacerbations, when high doses are often prescribed. However, patient concerns about potential side effects such as increased appetite, weight gain, and metabolic disturbances may reduce adherence, compromising treatment outcomes. While oral corticosteroids (OCSs) are well known to induce such effects, the metabolic impact of short-term high-dose ICSs remains poorly studied. Objective: This prospective pilot study aimed to assess whether a 14-day course of high-dose ICSs in adults with stable asthma induces changes in appetite, dietary intake, leptin levels, or body weight. Methods: Thirty-five adults (19 males, 16 females; mean age 48.7 ± 15.1 years) with stable mild asthma received ≥400 µg/day extrafine beclomethasone dipropionate/formoterol via pressurized metered-dose inhaler for 14 days. Participants underwent assessments at baseline and after 14 days, including body weight, BMI, fasting serum leptin levels, dietary intake (evaluated using 24 h dietary recalls), and appetite (measured via a visual analogue scale). Results: No significant changes were observed in body weight (mean change: −0.38 kg; 95% CI: −0.81 to 0.05; p = 0.083) or BMI (p = 0.912) following high-dose ICS use. Similarly, serum leptin levels (mean change: 0.13 ng/mL; 95% CI: −3.47 to 3.72; p = 0.945), subjective appetite scores (mean change: −4.93 mm; 95% CI: −13.64 to 3.79; p = 0.267), and dietary energy intake (mean change: +255 kJ/day; 95% CI: −380 to 891; p = 0.431) did not differ significantly post-intervention. Conclusions: Short-term high-dose ICS therapy in adults with mild asthma may not significantly affect appetite, dietary intake, leptin levels, or body weight. These findings support the metabolic safety of short-term high-dose ICSs and may help alleviate patient concerns, improving adherence during exacerbation management. Full article

Background and Clinical Significance: Bilateral diffuse uveal melanocytic proliferation (BDUMP) is a rare paraneoplastic syndrome characterized by bilateral uveal melanocyte proliferation and progressive visual disturbance. While most commonly associated with solid tumors, its occurrence in hematologic malignancies is exceedingly rare. Case Presentation: We report a case of BDUMP in a 64-year-old male recently diagnosed with chronic myelomonocytic leukemia (CMML), who presented with subacute, painless bilateral blurred vision. Multimodal imaging revealed suggestive features of BDUMP, including orange-red subretinal patches, retinal pigment epithelium mottling, and diffuse choroidal thickening, consistent with early structural involvement despite preserved central vision. No intraocular mass or signs of inflammation were observed. The patient did not receive specific treatment for BDUMP, and visual acuity remained stable during follow-up. Conclusions: This case underscores the importance of considering BDUMP in the differential diagnosis of bilateral visual symptoms in patients with hematologic malignancies. Although rare, BDUMP may occur in the context of CMML. Recognition through multimodal imaging and interdisciplinary collaboration is essential, and further research is needed to clarify its pathogenesis and improve management strategies. Full article

With the increase in the penetration rate of distributed sources and loads, the sensor monitoring data is increasing dramatically. Power grid maintenance services require a rapid response in power quality data analysis. To achieve a rapid response and highly accurate classification of power quality disturbances (PQDs), this paper proposes an efficient classification algorithm for PQDs based on Lissajous trajectory (LT) and a lightweight DenseNet, which utilizes the concept of Lissajous curves to construct an ideal reference signal and combines it with the original PQD signal to synthesize a feature trajectory with a distinctive shape. Meanwhile, to enhance the ability and efficiency of capturing trajectory features, a lightweight L-DenseNet skeleton model is designed, and its feature extraction capability is further improved by integrating an attention mechanism with L-DenseNet. Finally, the LT image is input into the fusion model for training, and PQD classification is achieved using the optimally trained model. The experimental results demonstrate that, compared with current mainstream PQD classification methods, the proposed algorithm not only achieves superior disturbance classification accuracy and noise robustness but also significantly improves response speed in PQD classification tasks through its concise visualization conversion process and lightweight model design. Full article

With the widespread adoption of mobile reading across diverse scenarios, understanding environmental impacts on attention has become crucial for reading performance optimization. Building upon this premise, the study examined the impacts of different reading environments on attention during mobile reading, utilizing a mixed-methods approach that combined eye-tracking experiments with semi-structured interviews. Thirty-two college students participated in the study. Quantitative attention metrics, including total fixation duration and fixation count, were collected through eye-tracking, while qualitative data regarding perceived environmental influences were obtained through interviews. The results indicated that the impact of different environments on mobile reading attention varies significantly, as this variation is primarily attributable to environmental complexity and individual interest. Environments characterized by multisensory inputs or dynamic disturbances, such as fluctuating noise and visual motion, were found to induce greater attentional dispersion compared to monotonous, low-variation environments. Notably, more complex potential task-like disturbances (e.g., answering calls, conversations) were found to cause the greatest distraction. Moreover, stimuli aligned with an individual’s interests were more likely to divert attention compared to those that did not. These findings contribute methodological insights for optimizing mobile reading experiences across diverse environmental contexts. Full article

Objective: The clinical presentation of inherited retinal dystrophies associated with pathogenic variants in PRPH2 is highly variable. Here we present bilateral sector macular dystrophy as a novel clinical phenotype. Methods and analysis: Ophthalmologic examination, detailed retinal imaging with optical coherence tomography (OCT), OCT-angiography, fundus and near-infrared autofluorescence and molecular genetic testing were performed on a 30-year-old female. Results: The patient reported the onset of subjective visual disturbances 4.5 months prior to our first examination. Clinical examination and retinal imaging revealed bilateral sharply demarcated paracentral lesions in the temporal lower macula and otherwise normal retinal findings. Patient history revealed no medication or other possible causes for these unusual retinal lesions. Molecular genetic testing revealed a heterozygous c.623G>A variation (p.(Gly208Asp)) in the PRPH2 gene. Conclusions: Bilateral sectoral macular dystrophy has not been reported previously in any inherited retinal dystrophy. This feature adds to the wide spectrum of PRPH2-associated clinical presentations. Full article

Reliable and accurate docking remains a fundamental challenge for autonomous mobile robots (AMRs) operating in complex industrial environments with dynamic lighting, motion blur, and occlusion. This study proposes a novel multi-sensor fusion-based docking framework that significantly enhances robustness and precision by integrating YOLOv8-based AprilTag detection, depth-aided 3D localization, and LiDAR-based orientation correction. A key contribution of this work is the construction of a custom AprilTag dataset featuring real-world visual disturbances, enabling the YOLOv8 model to achieve high-accuracy detection and ID classification under challenging conditions. To ensure precise spatial localization, 2D visual tag coordinates are fused with depth data to compute 3D positions in the robot’s frame. A LiDAR group-symmetry mechanism estimates heading deviation, which is combined with visual feedback in a hybrid PID controller to correct angular errors. A finite-state machine governs the docking sequence, including detection, approach, yaw alignment, and final engagement. Simulation and experimental results demonstrate that the proposed system achieves higher docking success rates and improved pose accuracy under various challenging conditions compared to traditional vision- or LiDAR-only approaches. Full article

Syncope of unclear cause (SUC) presents a significant diagnostic challenge, with a considerable proportion of patients remaining without a definitive diagnosis despite comprehensive clinical evaluation. This study aims to explore the potential of unsupervised machine learning (ML), specifically clustering algorithms, to identify clinically meaningful subgroups within a cohort of 123 patients with SUC. Patients were prospectively recruited from the cardiology, neurology, and emergency departments, and clustering was performed using the k-prototypes algorithm, which is suitable for mixed-type data. The number of clusters was determined through cost function analysis and silhouette index, and visual validation was performed using UMAP. Five distinct patient clusters were identified, each exhibiting unique profiles in terms of age, comorbidities, and symptomatology. After clustering, nocturnal cardiorespiratory polygraphy and heart rate variability (HRV) parameters were analyzed across groups to uncover potential physiological differences. The results suggest distinct autonomic and respiratory patterns in specific clusters, pointing toward possible links among sympathetic dysregulation, sleep-related disturbances, and syncope. While the sample size imposes limitations on generalizability, this pilot study demonstrates the feasibility of applying unsupervised ML to complex clinical syndromes. The integration of clinical, autonomic, and sleep-related data may provide a foundation for future, larger-scale studies aiming to improve diagnostic precision and guide personalized management strategies in patients with SUC. Full article

Cancer remains a major global health burden driven by complex biological mechanisms, and while targeted therapies like tyrosine kinase inhibitors (TKIs) have revolutionized treatment, their efficacy and safety are significantly influenced by drug–drug interactions (DDIs). Tyrosine-kinase receptors (RTKs) regulate critical cellular processes, and their dysregulation through mutations or overexpression drives oncogenesis, with TKIs designed to inhibit these aberrant signaling pathways by targeting RTK phosphorylation. Pharmacokinetic DDIs can critically impact the efficacy and safety of TKIs such as erlotinib, gefitinib, and pazopanib by affecting their absorption, distribution, and metabolism. The modification of pH can influence drug absorption; furthermore, the inhibition or induction of metabolizing enzymes may affect biotransformation, while distribution can be altered through the modulation of transmembrane transporters. Additionally, ensuring quality of life during TKI treatment requires vigilant monitoring and management of adverse events, which range from mild (e.g., rash, diarrhea, fatigue) to severe (e.g., hepatotoxicity, cardiotoxicity). Drug-specific toxicities, such as hyperlipidemia with lorlatinib or visual disturbances with crizotinib, must be assessed using specific criteria, with dose adjustments and supportive care tailored to individual patient responses. Thus, optimal TKI therapy relies on managing drug interactions through multidisciplinary care, monitoring, and patient education to ensure safety and treatment efficacy. Full article

This study presents a sustainable and adaptive approach to mineral processing. A hybrid intelligent control system was developed to beneficiate fine chromite ore in a jigging machine. The objective is to enhance separation efficiency and reduce chromium losses through real-time optimization of process parameters under variable feed conditions. The method addresses ore composition fluctuations by integrating three components: Physical modeling of particle motion, regression analysis, and neural network-based prediction. The jig bed level and pulsation frequency are used as control variables, while the Cr₂O₃ content in the feed ($C_r$) is treated as a disturbance. A neural network predicts the Cr₂O₃ content in the concentrate ($C_c$) and in the tailings ($C_t$), representing chromite-rich and gangue fractions, respectively. The optimization is performed using a constrained Interior-Point algorithm. The model demonstrates high predictive accuracy, with a mean squared error (MSE) below 0.01. The proposed control algorithm reduces chromium losses in tailings from 7.5% to 5.5%, while improving concentrate quality by 3–6%. A real-time human–machine interface (HMI) was developed in SIMATIC WinCC for process visualization and control. The hybrid framework can be adapted to other mineral processing systems by adjusting the model structure and retraining the neural network on new ore datasets. Full article

Due to the complexity of planning and constructing underground lines, construction challenges—such as close proximity and multi-line interactions—are increasingly being recognized, along with their associated safety hazards. The visual observation of tunnel deformation and changes in the surrounding strata is difficult. In this study, laboratory model experiments were conducted using a mixture of liquid paraffin, n-tridecane, and silica gel powder, combined in specific proportions to create a transparent material that simulates natural soft rock. The new tunnel was designed to simultaneously cross over and under two existing tunnels. The impact of the new tunnel on the existing tunnels was examined, with excavation length and soil layer thickness considered as the primary influencing factors. The results indicate that excavating the new tunnel causes settlement deformation in the tunnels above and heave deformation in the tunnels below. The magnitude of deformation increases as excavation progresses but decreases with the greater thickness of the soil interlayer. For an existing tunnel, variations in the thickness of the soil interlayer not only affect its own deformation but also disturb the tunnel on the opposite side. Therefore, to ensure safer and orderly urban tunnel construction and to address the “black box” effect, it is essential to study the deformation characteristics of existing tunnels and their surrounding rock during the construction of new tunnels. Full article

Objective: Central neurocytomas (CNs), classified as CNS (central nervous system) grade 2 tumors, are exceptionally rare tumors, accounting for approximately 0.1–0.5% of all intracranial neoplasms, and are typically characterized by a benign clinical course and frequent association with hydrocephalus. This study aims to present a comprehensive analysis of surgical and adjuvant therapies for CN. Methods: The study comprised all patients who underwent microsurgical tumor removal in our center over the past decade (2013–2023). Clinical manifestations, surgical and adjuvant therapy approaches, MRI and histological findings, clinical outcomes, and recurrence-free survival were evaluated. Results: A total of eleven patients (six men, mean age of 28.0 years; five women, mean age of 53.6 years) underwent surgical treatment. Intraventricular tumors were the most common (72.7%, n = 8). The predominant presenting symptoms were headache and visual disturbances. All tumors exhibited contrast enhancement on MRI. Hydrocephalus was present in five patients. The Ki67 proliferation index ranged from 2% to 10%, with nine patients exhibiting Ki67 > 3%. The median recurrence-free survival was 38.0 months (IQR: 25.0–53.0). The most severe postoperative complications included aphasia, hemiparesis, and memory impairment, resulting in a postoperative Karnofsky Performance Status (KPS) below 70% in five patients. Follow-up assessments showed significant symptomatic improvement in all affected patients. Conclusions: Gross total resection is the recommended first-line therapy with favorable neurological outcomes and for atypical CN as well. Adjuvant radiotherapy should be reserved for tumor progression and recurrence. The role of adjuvant chemotherapy remains unclear, but it may be an option for CN with a high proliferation index. Full article

Objectives: The aims of the presented study were to investigate and compare the effectiveness of Low-Level Laser Therapy (LLLT) and therapeutic ultrasound (US) on pain, function, emotional status, and sleep disturbances in patients with rotator cuff tendinopathy (RCT). Method: A total of 84 patients with RCT were included in the study and randomly divided into the US group (n = 42) and the LLLT group (n = 42). Hot-pack, transcutaneous electrical nerve stimulation, and a home-based exercise program were also administered to patients in each group. The patients were evaluated at baseline, and at 1st, 4th, and 12th weeks after treatment by Visual Analog Scale (VAS), Shoulder Pain and Disability Index (SPADI), Constant Murley Score (CMS), Disabilities of the Arm, Shoulder, and Hand Questionnaire (DASH), Hand Grip Strength (HGS), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Pittsburgh Sleep Quality Index (PSQI), and Short Form-36 (SF-36). Results: Significant improvements in VAS, SPADI, CMS, DASH, BDI, BAI, PSQI, and SF-36 scores were observed over time in both groups (p < 0.05 for all). The improvements in HGS scores were significantly greater in the US group compared to the LLLT group (p < 0.05 for all). There were no statistically significant differences between the groups in VAS, SPADI, CMS, DASH, BDI, BAI, PSQI, and SF-36 scores at each time point (p > 0.05 for all). Conclusions: Both therapeutic US and LLLT are effective and safe in the treatment of patients with RCT. However, our findings indicate no superiority of one treatment over the other in terms of pain relief or improvements in function, emotional status, sleep disturbances, or quality of life. Full article

Light Detection and Ranging (LiDAR) point clouds are an essential perception modality for artificial intelligence systems like autonomous driving and robotics, where the ubiquity of small objects in real-world scenarios substantially challenges the visual tracking of small targets amidst the vastness of point cloud data. Current methods predominantly focus on developing universal frameworks for general object categories, often sidelining the persistent difficulties associated with small objects. These challenges stem from a scarcity of foreground points and a low tolerance for disturbances. To this end, we propose a deep neural network framework that trains a Siamese network for feature extraction and innovatively incorporates two pivotal modules: the target-awareness prototype mining (TAPM) module and the regional grid subdivision (RGS) module. The TAPM module utilizes the reconstruction mechanism of the masked auto-encoder to distill prototypes within the feature space, thereby enhancing the salience of foreground points and aiding in the precise localization of small objects. To heighten the tolerance of disturbances in feature maps, the RGS module is devised to retrieve detailed features of the search area, capitalizing on Vision Transformer and pixel shuffle technologies. Furthermore, beyond standard experimental configurations, we have meticulously crafted scaling experiments to assess the robustness of various trackers when dealing with small objects. Comprehensive evaluations show our method achieves a mean Success of 64.9% and 60.4% under original and scaled settings, outperforming benchmarks by +3.6% and +5.4%, respectively. Full article