Additional file 1: of Combined femoral and sciatic nerve block versus femoral and local infiltration anesthesia for pain control after total knee arthroplasty: a meta-analysis of randomized controlled trials

The search strategy of the included studies. (DOCX 14 kb

Additional file 3: of Combined femoral and sciatic nerve block versus femoral and local infiltration anesthesia for pain control after total knee arthroplasty: a meta-analysis of randomized controlled trials

The results of VAS with rest at 12 h, 24 h and 48 h after excluded the study of Safa B. (TIF 3014 kb

Pheochromocytoma-induced diffuse alveolar hemorrhage after cholecystectomy: A case report and literature review

Diffuse alveolar hemorrhage (DAH) can be caused by various conditions, categorized as autoimmune and non-autoimmune. Immunofactor-mediated vasculitis, such as Wegener granulomatosis, microscopic polyangiitis, Goodpasture syndrome, connective tissue disorders, and antiphospholipid antibody syndrome, are common autoimmune causes. Non-autoimmune factors include infectious or toxic exposures and neoplastic conditions. The diagnosis of DAH, resulting from excessive catecholamine release from an adrenal pheochromocytoma or extra-adrenal paraganglioma, can present diagnostic challenges and necessitate prompt treatment. In this report, we present a case of pheochromocytoma that manifested as an adrenal incidentaloma (diagnosed during the management of sudden-onset DAH after cholecystectomy). Case report: A 39-year-old female patient with adrenal incidentaloma developed DAH following a cholecystectomy procedure, presenting with sudden-onset hemoptysis and dyspnea. Administration of glucocorticoids, known to precipitate pheochromocytoma crisis (PCC), was required before the cause was determined. Intubation and mechanical ventilation were necessary due to persistent hypoxemic respiratory failure and acute respiratory distress syndrome (ARDS). The patient in this case experienced two epidoses of PCC while she was on mechanical ventilation. Subsequent work-up revealed a 26 × 25 mm left adrenal adenoma with hormonal confirmation of catecholamine hypersecretion. A laparoscopic adrenalectomy was done eight months later to excise the left adrenal gland. Subsequent examination of the tissue revealed pheochromocytoma, thereby validating the initial diagnosis. Conclusion: Adrenal incidentalomas may be pheochromocytomas (adrenal incidentalomas can manifest as pheochromocytomas), even without adrenergic symptoms. It is recommended that adrenal incidentalomas undergo evaluation for pheochromocytoma before undergoing invasive surgery or receiving corticosteroid treatment. When considering potential causes of DAH without further elucidation, including a pheochromocytoma or paraganglioma (PPGLs) in the differential diagnosis is important

ForestSemantic: a dataset for semantic learning of forest from close-range sensing

Information about trees in forest is essential for the assessment of the quantity and the quality of forest ecosystem services. Recently, Deep Learning (DL) methods were regarded as a new cornerstone of algorithm development. Semantic annotations of 3D forest scenes are fundamental for DL algorithm developments. Its necessity has become more urgent as DL is data-driven and requires large amount of training and verification data. However, high-quality annotated forest datasets are still rare, as trees comprise of irregular structures and small components and pose significantly greater challenges even for manual recognition in comparison with artificial objects. This paper introduces a new open point cloud dataset ForestSemantic for forest semantic studies at both individual tree- and plot-levels. The dataset is based on TLS data with different forest conditions. Manual annotation was carried out to a level of detail 4, i.e., until all visible branches. Semantic information is provided at both plot- and tree-levels, as well as at both object- and point-level. Thus, the dataset supports both instance and semantic studies, such as objects detection and segmentation and classification at both tree- and plot-levels. In addition, the dataset also provides comprehensive structural tree traits as reference for further methodological development and verification. This dataset is expected to facilitate research in new dimensions and benchmarks of different systems and solutions. A few examples are demonstrated in this paper to unveil the potentials of the dataset for various applications. In future, it is also possible to simulate other types of point clouds by down-sampling and deforming, and to transfer the dataset for training and verification of other close-range sensing systems, as the dataset was generated using TLS point clouds that represent the highest spatial resolution and geometric accuracy in all close-range point clouds

Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements

Abstract Background Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117–5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) - borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys. Results The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions. Conclusions This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations