A novel subtype classification and corresponding surgical strategies for spinal dural cysts -a report of 104 cases.

BACKGROUND: The nomenclature, classification, and surgical approaches for spinal dural cysts (SDCs) remain a subject of controversy. PURPOSE: The present study proposes a novel subtype classification system and corresponding surgical strategies, with the aim of enhancing comprehension of this entity and standardizing surgical treatment. STUDY DESIGN: A retrospective review. PATIENT SAMPLE: A total of 104 patients with SDCs underwent novel subtype classification and corresponding surgical strategies from January 2015 to December 2021. Fifty-four patients who underwent conventional surgery from January 2012 to December 2014 as the control group for preliminary validation. OUTCOME MEASURES: The outcomes are categorized into four levels: excellent, good, unchanged, and deteriorated, based on neurological improvement and pain relief. Grades of excellent and good were identified as improvements. Follow-up magnetic resonance imaging and complications were also evaluated. METHODS: Based on the shared pathogenic factor of dural defects, the dural-associated cysts in the spinal canal are uniformly referred to as SDCs. They are further classified into Type 1 (no nerve roots) and Type 2 (containing nerve roots), with four additional subtypes based on the shape of the leak and the flow of leakage. The fissure-shaped leak of Type 1a SDCs is directly sutured, whereas the aperture-shaped leak of Type 1b is repaired using a patch. Low-flow leakage of Type 2a is directly sealed using a combination of adipose tissue and fibrin glue, whereas high-flow Type 2b necessitates suturing at the end of the leak to attenuate cerebrospinal fluid flow prior to sealing. RESULTS: The follow-up period averaged 23.8 months. Excellent or good outcomes were achieved in 100%, 88.9%, 100%, and 97.3% for the four subtypes respectively. The overall improvement rate of SDCs was 97.1%, which was significantly higher than that of the conventional surgery group (85.2%, p=0.008). MRI follow-up showed a significant reduction in cyst size of 100%, 100%, 97.8%, and 97.3% for the four subtypes, respectively. The primary complications included pseudomeningocele in 4 cases (3.8%) and delayed wound healing in 5 cases (4.8%). The complication rate was also significantly lower than that of the control group (8.7% vs 24.1%, p=0.008). CONCLUSIONS: Subtyping SDCs based on the variation of leaks and leakage can enable more targeted surgical strategies, which are helpful for improving treatment effectiveness and reducing complications.

MATI: Multimodal Adaptive Tracking Integrator for Robust Visual Object Tracking.

Visual object tracking, pivotal for applications like earth observation and environmental monitoring, encounters challenges under adverse conditions such as low light and complex backgrounds. Traditional tracking technologies often falter, especially when tracking dynamic objects like aircraft amidst rapid movements and environmental disturbances. This study introduces an innovative adaptive multimodal image object-tracking model that harnesses the capabilities of multispectral image sensors, combining infrared and visible light imagery to significantly enhance tracking accuracy and robustness. By employing the advanced vision transformer architecture and integrating token spatial filtering (TSF) and crossmodal compensation (CMC), our model dynamically adjusts to diverse tracking scenarios. Comprehensive experiments conducted on a private dataset and various public datasets demonstrate the model's superior performance under extreme conditions, affirming its adaptability to rapid environmental changes and sensor limitations. This research not only advances visual tracking technology but also offers extensive insights into multisource image fusion and adaptive tracking strategies, establishing a robust foundation for future enhancements in sensor-based tracking systems.

Preparation and properties of thermoplastic starch under the synergism of ultrasonic and elongational rheology.

Thermoplastic starch, as an eco-friendly alternative to petroleum-based plastics, possesses numerous advantages, including cost-effectiveness, complete biodegradability, and renewable sourcing. Nevertheless, the plasticizer dispersion and starch plasticization efficiency are poor via the processing method dominate by shear deformation. Thus, the aim of this study is proposing a new approach combining ultrasonic treatment and elongational rheology to prepare thermoplastic starch and evaluate its properties. This innovative approach facilitated the production of thermoplastic starch with glycerol as the plasticizer at varying rotor speeds. Furthermore, this study was carried out by using a self-developed ultrasonic-assisted vane mixer (UVM) based on elongational flow. The samples were analyzed using FTIR, WAXD, polarized optical microscope, dynamic rheometer, universal testing machine and thermogravimetric analysis. FTIR and dynamic rheological analysis showed that elongational rheology and ultrasonics stimulate hydrogen bond formation between starch and glycerol, elevating starch thermoplasticity. Tensile tests and thermogravimetric analysis highlighted that high-intensity elongational field improved the mechanical properties and thermal stability of the thermoplastic starch. Additionally, the incorporation of ultrasonic treatment yielded further improvements, yielding remarkable tensile strength (6.09 MPa) and elongation at break (139.3 %). This synergistic interplay between ultrasonics and elongational rheology holds immense potential for advancing thermoplastic starch manufacturing.