Search Results (324)

Background: Hyaluronic acid (HA) fillers offer a minimally invasive alternative for breast augmentation, appealing to young female patients seeking natural results and minimal recovery time. However, achieving optimal outcomes requires a thorough understanding of breast anatomy, filler properties, and safe injection techniques. This study provides a comprehensive analysis of the anatomical considerations, techniques, and filler properties necessary for optimal breast augmentation using HA filler. It also explores patient selection, long-term safety and efficacy, and the management of complications. A review of key anatomical structures, including glandular tissue, fascial layers, vascular anatomy, and Cooper’s ligaments was conducted. Injection techniques, such as dual-plane and submuscular approaches, were analysed with a focus on pre-procedural imaging. Four cases of young female patients undergoing breast augmentation using HA filler (e.p.t.q. eve X, Jetema Inc., Seoul, Republic of Korea) were analysed. The efficacy of HA fillers in achieving natural breast enhancement was demonstrated in all four cases. Ultrasound played a crucial role in ensuring accurate filler placement, reducing risks like vascular occlusion and filler migration. Patients reported high satisfaction and minimal complications, though periodic treatments were required for maintenance. HA filler-based breast augmentation is a safe and effective option for young female patients, delivering natural results with rapid recovery. Although the results can be temporary and maintenance treatment is required, HA fillers may offer a non-invasive alternative to silicone implants. Optimal outcomes can be achieved through a thorough understanding of anatomy, the use of highly cohesive fillers, and ultrasound-guided injection techniques. Full article

Bank fraud detection faces critical challenges in imbalanced datasets, where fraudulent transactions are rare, severely impairing model generalization. This study proposes a Gaussian noise-based augmentation method to address class imbalance, contrasting it with SMOTE and ADASYN. By injecting controlled perturbations into the minority class, our approach mitigates overfitting risks inherent in interpolation-based techniques. Five classifiers, including XGBoost and a convolutional neural network (CNN), were evaluated on augmented datasets. XGBoost achieved superior performance with Gaussian noise-augmented data (accuracy: 0.999507, AUC: 0.999506), outperforming SMOTE and ADASYN. These results underscore Gaussian noise’s efficacy in enhancing fraud detection accuracy, offering a robust alternative to conventional oversampling methods. Our findings emphasize the pivotal role of augmentation strategies in optimizing classifier performance for imbalanced financial data. Full article

This study investigated the mechanisms influencing hydraulic fracture propagation under the influence of cleat complex geometries. The study established a 3D-DEM (three-dimensional discrete element method) model for complex fracture propagation, utilizing the discrete element method and incorporating complex cleat geometries. The model simulates the propagation patterns of hydraulic fractures within coal seams. The findings indicate the following: (1) The fracture width within coal seam cleats undergoes significant variations. A quantification method for these variations and a novel concept of cleat-induced fracture deflection angle are proposed. As the cleat angle increases from 0° to 45°, the cleat-induced fracture deflection angle also increases, reaching 17.1°, demonstrating that cleats have a directional inducing effect on hydraulic fracture propagation; (2) injection hole pressure decreases during fracture capture by coal cleats, whereas pressure escalation occurs during penetration through these cleats; (3) a smaller angle between the face cleat orientation and the direction of maximum principal stress results in longer fracture lengths and narrower fracture widths; and (4) higher injection rates augment the fracture width, facilitating the entry of proppants. Full article

Objective: To investigate whether the regular administration of blueberry extract and low-intensity resistance exercise training (RT), either alone or in combination, during the development of monocrotaline (MCT)-induced severe pulmonary arterial hypertension (PAH) in rats protect the left ventricle (LV) from redox dysregulation and pathological remodeling. Methods: Groups of seven male Wistar rats were formed for the experiment: sedentary control; sedentary hypertensive; sedentary hypertensive blueberry; exercise hypertensive; and exercise hypertensive blueberry. PAH was experimentally induced through a single intraperitoneal administration of MCT at a dose of 60 mg/kg. One day after injection, the blueberry groups started receiving a daily dose of blueberry extract (100 mg/kg) by gavage, while the exercise groups initiated a three-week program of RT (ladder climbing; 15 climbs carrying 60% of maximum load; one session/day; 5 times/week). Echocardiographic evaluations were conducted 23 days after injection, and the rats were euthanized the next day to harvest LV tissue. Results: Separately, blueberry extract and RT mitigated augments in pulmonary artery resistance, LV tissue redox dysregulation (i.e., increased PC levels) and detrimental remodeling (i.e., reduced inflammation), and reductions in ejection fraction (EF) and fractional shortening (FS) caused by PAH. The combination of treatments prevented reductions in EF and FS, along with the development of a D-shaped LV. Conclusions: blueberry extract and moderate-intensity resistance training administered during the development of MCT-induced severe PAH in rats prevented LV redox dysregulation and pathological remodeling, thereby preserving its function. Full article

Lip augmentation using hyaluronic acid (HA) fillers has become one of the most popular non-surgical aesthetic procedures, yet it is not without risks, particularly vascular complications. This study explores a novel vertical injection technique for submucosal placement of HA fillers, designed to enhance safety and achieve natural-looking outcomes. Ten patients underwent lip augmentation using the proposed technique, which involved ultrasound-guided injections at predefined entry points to target intralabial compartments while minimizing the risk of labial artery injury. The results demonstrated high patient satisfaction, with significant improvements in lip volume and contour. The submucosal placement yielded subtle, natural results with fewer visible irregularities compared to superficial injections. No major complications, such as vascular occlusion, were observed, and minor side effects, including transient swelling and redness, resolved within 48 h. The use of ultrasound imaging allowed precise filler placement and reduced the risks associated with traditional horizontal injection paths parallel to the labial arteries. While the findings highlight the technique’s potential in terms of safety and efficacy, limitations include the small sample size, short-term follow-up, and the absence of a control group. Further studies with larger cohorts and comparative analyses are needed to validate long-term outcomes. This innovative approach underscores the importance of anatomical precision and advanced imaging technologies in enhancing safety and aesthetic outcomes in lip augmentation. Full article

Aiming at the overfitting problem caused by the limited sample size in the spectral classification of aero-engine hot jets, this paper proposed a synthetic spectral enhancement classification network FTIR-SpectralGAN for the FT-IR of aeroengine hot jets. Firstly, passive telemetry FTIR spectrometers were used to measure the hot jet spectrum data of six types of aero-engines, and a spectral classification dataset was created. Then, a spectral classification network FTIR-SpectralGAN was designed, which consists of a generator and a discriminator. The generator architecture comprises six Conv1DTranspose layers, with five of these layers integrated with BN and LeakyReLU layers to introduce noise injection. This design enhances the generation capability for complex patterns and facilitates the transformation from noise to high-dimensional data. The discriminator employs a multi-task dual-output structure, consisting of three Conv1D layers combined with LeakyReLU and Dropout techniques. This configuration progressively reduces feature dimensions and mitigates overfitting. During training, the generator learns the underlying distribution of spectral data, while the discriminator distinguishes between real and synthetic data and performs spectral classification. The dataset was randomly partitioned into training, validation, and test sets in an 8:1:1 ratio. For training strategy, an unbalanced alternating training approach was adopted, where the generator is trained first, followed by the discriminator and then the generator again. Additionally, weighted mixed loss and label smoothing strategies were introduced to enhance network training performance. Experimental results demonstrate that the spectral classification accuracy reaches up to 99%, effectively addressing the overfitting issue commonly encountered in CNN-based classification tasks with limited samples. Comparative experiments show that FTIR-SpectralGAN outperforms classical data augmentation methods and CVAE-based synthetic data enhancement approaches. It also achieves higher robustness and classification accuracy compared to other spectral classification methods. Full article

The tomato is among the crops with the most extensive cultivated area and greatest consumption in our nation; nonetheless, secondary salinization of facility soil significantly hinders the sustainable growth of facility agriculture. Melatonin (MT), as an innovative plant growth regulator, is essential in stress responses. This research used a hydroponic setup to replicate saline stress conditions. Different endogenous levels of melatonin (MT) were established by foliar spraying of 100 μmol·L⁻¹ MT, the MT synthesis inhibitor p-CPA (100 μmol·L⁻¹), and a combination of p-CPA and MT, to investigate the mechanism by which MT mitigates the effects of salt stress on the photosynthetic efficiency of tomato seedlings. Results indicated that after six days of salt stress, the endogenous MT content in tomato seedlings drastically decreased, with declines in the net photosynthetic rate and photosystem performance indices (PI_total and PI_abs). The OJIP fluorescence curve exhibited distortion, characterized by anomalous K-band and L-band manifestations. Exogenous MT dramatically enhanced the gene (TrpDC, T5H, SNAcT, and AcSNMT) expression of critical enzymes in MT synthesis, therefore boosting the level of endogenous MT. The application of MT enhanced the photosynthetic parameters. MT treatment decreased the fluorescence intensities of the J-phase and I-phase in the OJIP curve under salt stress, attenuated the irregularities in the K-band and L-band performance, and concurrently enhanced quantum yield and energy partitioning ratios. It specifically elevated φP_o, φE_o, and ψ_o, while decreasing φD_o. The therapy enhanced parameters of both the membrane model (ABS/RC, DI_o/RC, ET_o/RC, and TR_o/RC) and leaf model (ABS/CS_m, TR_o/CS_m, ET_o/CS_m, and DI_o/CS_m). Conversely, the injection of exogenous p-CPA exacerbated salt stress-related damage to the photosystem of tomato seedlings and diminished the beneficial effects of MT. The findings suggest that exogenous MT mitigates salt stress-induced photoinhibition by (1) modulating endogenous MT concentrations, (2) augmenting PSII reaction center functionality, (3) safeguarding the oxygen-evolving complex (OEC), (4) reinstating PSI redox potential, (5) facilitating photosynthetic electron transport, and (6) optimizing energy absorption and dissipation. As a result, MT markedly enhanced photochemical performance and facilitated development and salt stress resilience in tomato seedlings. Full article

Background: Referred pain frequently co-exists with visceral pain. However, the exact mechanism governing referred somatic hyperalgesia remains elusive. Methods: By injecting 20% acetic acid into the stomach, we established a mouse model of gastric ulcer (GU). Hematoxylin and eosin (H&E) staining was used as the evaluation criterion for the gastric ulcer model. Evan’s blue (EB) and von Frey tests detected the somatic sensitized area. The DRG neurons distributed among the spinal segments of the sensitized area were prepared for biochemical and electrophysiological experiments. The CCR2 antagonist was intraperitoneally (i.p.) injected into GU mice to test the effect of blocking CCR2 on somatic neurogenic inflammation. Results: GU not only instigated neurogenic plasma extravasation and referred somatic allodynia in the upper back regions spanning the T9 to T11 segments but also augmented the co-expression of T-type Ca²⁺ channels and CCR2 and led to the gating properties of T-type Ca²⁺ channel alteration in T9–T11 small-diameter DRG neurons. Moreover, the administration of the CCR2 antagonist inhibited the T-type Ca²⁺ channel activation, consequently mitigating neurogenic inflammation and referred somatic hyperalgesia. The application of the CCR2 agonist to normal T9–T11 small-diameter DRG neurons simulates the changes in the gating properties of T-type Ca²⁺ channel that occur in the GU group. Conclusions: Therefore, these findings indicate that CCR2 may function as a critical regulator in the generation of neurogenic inflammation and mechanical allodynia by modulating the gating properties of the T-type Ca²⁺ channels. Full article

Radioresistance remains a major obstacle in cervical cancer treatment, frequently engendering tumor relapse and metastasis. However, the details of its mechanism of action remain largely enigmatic. This study delineates the prospective impacts of short-form human T-cell lymphoma invasion and metastasis 2 (TIAM2S) involving the radiation resistance of cervical cancer. In this study, we established three pairs of radioresistant (RR) cervical cancer cells (HeLa, C33A and CaSki) and their parental wild-type (WT) cells. We revealed a consistent augmentation of TIAM2S, but not long-form human T-cell lymphoma invasion and metastasis 2 (TIAM2L) were displayed in RR cells that underwent a 6 Gy radiation administration. Remarkably, RR cells exhibited decreased radiosensitivity and abridged apoptosis, as estimated through a clonogenic survival curve assay and Annexin V/Propidium Iodide apoptosis assay, respectively. TIAM2S suppression increased radiosensitivity and enhanced cell apoptosis in RR cells, whereas its forced introduction modestly abolished radiosensitivity and diminished WT cell apoptosis. Furthermore, TIAM2S overexpression notably aggravated RR cell migration, whereas its blockage reduced WT cell mobilities, as confirmed by an in vitro time-lapse recording assay. Notably, augmented lung localization was revealed after a tail-vein injection of CaSki-RR cells using the in vivo short-term lung locomotion BALB/c nude mouse model. TIAM2S impediment notably reduced radioresistance-increased lung locomotion. This study provides evidence that TIAM2S may operate as an innovative signature in cervical cancer that is resistant to radiotherapy. It displays multi-faceted roles including radioprotection, restricting apoptosis, promoting cell proliferation, and escalating cell migration/metastasis. Targeting TIAM2S, together with conventional radiotherapy, may be an innovative strategy for intensifying radiosensitivity and protecting against subsequent uncontrolled tumor growth and metastasis in cervical cancer treatment. Full article

This study proposes a novel framework using graph convolutional networks to analyze and interpret X-ray diffraction patterns, addressing challenges in phase identification for multi-phase materials. By representing X-ray diffraction patterns as graphs, the framework captures both local and global relationships between diffraction peaks, enabling accurate phase identification even in the presence of overlapping peaks and noisy data. The framework outperforms traditional machine learning models, achieving a precision of 0.990 and a recall of 0.872. This performance is attained with minimal hyperparameter tuning, making it scalable for large-scale material discovery applications. Data augmentation, including synthetic data generation and noise injection, enhances the model’s robustness by simulating real-world experimental variations. However, the model’s reliance on synthetic data and the computational cost of graph construction and inference remain limitations. Future work will focus on integrating real experimental data, optimizing computational efficiency, and exploring lightweight architectures to improve scalability for high-throughput applications. Full article

Lip augmentation has become increasingly popular in aesthetic medicine, driven by advancements in dermal filler technologies and injection techniques. This review provides a comprehensive overview of lip anatomy, age-related changes, and current best practices in lip augmentation using dermal fillers. The complex structure of the lips, including multiple layers of skin, muscle, and mucosa, contributes to their unique appearance and function. Age-related changes, such as volume loss, thinning of the vermilion border, and flattening of the philtrum, significantly impact lip aesthetics. Understanding these changes is crucial for developing effective treatment strategies. The review discusses the importance of tailoring treatments to individual patient needs, considering factors such as ethnic variations in lip structure and cultural preferences. It emphasizes the significance of proper filler selection, with hyaluronic acid-based products being the gold standard due to their biocompatibility and reversibility. Injection techniques, including needle and cannula approaches, are described in detail, with a focus on safety and optimal aesthetic outcomes. Anatomical considerations, particularly the vascular supply to the lips, are highlighted as critical for avoiding complications during filler injections. The review also addresses the evolving approach to lip augmentation, which now focuses on restoring natural contours and addressing age-related changes in the perioral region rather than simply increasing volume. Finally, the importance of managing patient expectations and the potential for future advancements in the field are discussed, including the development of more targeted filler products and refined injection techniques. Full article

The deep shale gas resources of the Sichuan Basin are abundant and constitute an important component of China’s natural gas production. Complicated by fault zones and other geostructures, the in situ stress state of the deep shale gas reservoirs in the Luzhou block remains poorly understood. This study integrated multiple datasets, including acoustic logging, diagnostic fracture injection testing (DFIT), imaging logging, and laboratory stress measurements, for calibration and constraint. A high-precision geomechanical model of the Luzhou block was constructed using the finite element method. This model characterizes the geomechanical properties of the reservoir and explores its applications in optimizing shale gas horizontal well placement, drilling processes, and fracture design. The study findings indicate that the Longmaxi Formation reservoir demonstrates abnormally high pore pressure, with gradients ranging from 16.7 to 21.7 kPa/m. The predominant stress regime is strike-slip, with an overburden stress gradient of 25.5 kPa/m and a minimum horizontal principal stress gradient ranging from 18.8 to 24.5 kPa/m. Based on a three-dimensional geomechanical model, a quantitative delineation of areas conducive to density reduction and pressure control drilling was conducted, and field experiments were implemented in well Y65-X. Utilizing an optimized drilling fluid density of 1.85 g/cm³, the deviated horizontal section was completed in a single trip, resulting in a 67% reduction in the drilling cycle compared to adjacent wells. Similarly, the Y2-X well demonstrated a test daily output of 506,900 cubic meters following an optimization of segmentation clustering and fracturing parameters. Studies indicate that 3D geomechanical modeling, informed by multi-source data constraints, can markedly enhance model precision, and such geomechanical models and their results can effectively augment drilling operational efficiency, elevate single-well production, and are advantageous for development. Full article

To reduce the significant time and cost associated with wind turbine blade fatigue testing, the applicability of the deep learning model Neural Basis Expansion Analysis (N-BEATS) for modeling the stiffness degradation of wind turbine blades was investigated. First, on the basis of a traditional blade stiffness degradation model, the stiffness data were expanded to meet the data volume requirements of N-BEATS. Second, the basic block structure of N-BEATS was improved (by treating the sequence-to-sequence prediction problem as a nonlinear multivariate regression problem) to meet the specific prediction requirements of this task, and the Pinball Mean Absolute Percentage Error (Pinball-MAPE) loss function was adopted to further reduce bias during the prediction process. Additionally, two data augmentation methods—time series combination and random noise injection—were applied to mitigate the risk of model overfitting and improve prediction accuracy. Experimental results demonstrated that the model can effectively learn underlying patterns in the stiffness data and successfully predict the remaining stiffness. Full article

Due to the challenge of acquiring abundant labeled samples, semi-supervised change detection (SSCD) approaches are becoming increasingly popular in tackling CD tasks with limited labeled data. Despite their success, these methods tend to come with complex network architectures or cumbersome training procedures, which also ignore the domain gap between the labeled data and unlabeled data. Differently, we hypothesize that diverse perturbations are more favorable to exploit the potential of unlabeled data. In light of this spirit, we propose a novel SSCD approach based on Weak–strong Augmentation and Class-balanced Sampling (WACS-SemiCD). Specifically, we adopt a simple mean-teacher architecture to deal with labeled branch and unlabeled branch separately, where supervised learning is conducted on the labeled branch, while weak–strong consistency learning (e.g., sample perturbations’ consistency and feature perturbations’ consistency) is imposed for the unlabeled. To improve domain generalization capacity, an adaptive CutMix augmentation is proposed to inject the knowledge from the labeled data into the unlabeled data. A class-balanced sampling strategy is further introduced to mitigate class imbalance issues in CD. Particularly, our proposed WACS-SemiCD achieves competitive SSCD performance on three publicly available CD datasets under different labeled settings. Comprehensive experimental results and systematic analysis underscore the advantages and effectiveness of our proposed WACS-SemiCD. Full article

Objective: In this study, we analyzed the existing chin augmentation methods and evaluated the effectiveness of using a subplatysmal fat autograft for augmenting insufficient chin projection. Materials and Methods: From January 2017 to December 2023, we studied 170 patients at the Department of Plastic Surgery, Sechenov First Moscow State Medical University, who presented with insufficient chin projection, localized fat deposits in the cervico-mental area, and age-related changes in the lower third of the face. The patients were divided into two groups: Group 1 (n = 93) consisted of patients who underwent chin augmentation using implants (Silastic, Medpor); Group 2 (n = 77) included patients who underwent medial platysmaplasty and chin augmentation using a fat autograft (subplatysmal autograft). Results: Chin augmentation was performed on all the patients with varying degrees of insufficient chin projection. The mean age was 36.5 ± 2 years. The average follow-up period was 18.9 months (range: 2–45 months). For chin augmentation using implants (Silastic, Medpor), +chin projection increases were observed as follows: 1.1–1.2 cm at 3 months, 0.9–2.3 cm at 6 months, and 0.8–1.7 cm at 12 months. The complications in this group included inflammatory processes in 7 (8%) patients, hematomas in 6 (6%) patients, and contour asymmetry in 13 (14%) patients. In the group that underwent chin augmentation with a subplatysmal fat autograft, the chin projection increased by 0.8–1.2 cm at 3 months, 0.7–1.3 cm at 6 months, and 0.6–1.9 cm at 12 months. The mean age was 38.3 ± 7 years, with an average follow-up of 18.3 months (range: 2–43 months). No infectious–inflammatory complications were observed. Aesthetic complications were noted in 14 (18%) patients. Conclusions: Among the existing methods for chin augmentation, many still consider osseous genioplasty to give more predictable results. However, its traumatic nature and lengthy rehabilitation period prompt surgeons to seek effective yet less invasive alternatives. When selecting a minimally invasive method for chin augmentation, preference is given to fat injections (lipofilling) and intraoperative use of autologous fat grafts. Augmentation using subplatysmal autologous fat grafts is a minimally invasive, safe, predictable, and long-lasting method for chin correction. Full article