Hybrid and Oriented Harmonic Potentials for Safe Task Execution in Unknown Environment

Harmonic potentials provide globally convergent potential fields that are provably free of local minima. Due to its analytical format, it is particularly suitable for generating safe and reliable robot navigation policies. However, for complex environments that consist of a large number of overlapping non-sphere obstacles, the computation of associated transformation functions can be tedious. This becomes more apparent when: (i) the workspace is initially unknown and the underlying potential fields are updated constantly as the robot explores it; (ii) the high-level mission consists of sequential navigation tasks among numerous regions, requiring the robot to switch between different potentials. Thus, this work proposes an efficient and automated scheme to construct harmonic potentials incrementally online as guided by the task automaton. A novel two-layer harmonic tree (HT) structure is introduced that facilitates the hybrid combination of oriented search algorithms for task planning and harmonic-based navigation controllers for non-holonomic robots. Both layers are adapted efficiently and jointly during online execution to reflect the actual feasibility and cost of navigation within the updated workspace. Global safety and convergence are ensured both for the high-level task plan and the low-level robot trajectory. Known issues such as oscillation or long-detours for purely potential-based methods and sharp-turns or high computation complexity for purely search-based methods are prevented. Extensive numerical simulation and hardware experiments are conducted against several strong baselines.Comment: 16 pages, 13 figure

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions

BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions

Lipidomics and Transcriptomics Differ Liposarcoma Differentiation Characteristics That Can Be Altered by Pentose Phosphate Pathway Intervention

Liposarcoma (LPS) is a rare and heterogeneous malignancy of adipocytic origin. Well-differentiated liposarcoma (WDLPS) and dedifferentiated liposarcoma (DDLPS) are two of the most common subtypes, showing similar genetic characterizations but distinct biological behaviors and clinical prognosis. Compared to WDLPS, DDLPS is more aggressive and has the potential of metastasis, as the malignant adipocytic tumor’s metabolic changes may have taken place during the tumorigenesis of LPSs. Therefore, to investigate the lipid alterations between the two subtypes, high-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS) based untargeted lipidomic analysis was performed onto LPS tissues from 6 WDLPS and 7 DDLPS patients. The lipidomic analysis showed the upregulated phosphatidylcholines and phosphoethanolamines in DDLPS, and the upregulated triglycerides and diglycerides in WDLPS, which might be due to the uncompleted adipocytic dedifferentiation leading to such tumorigenesis. Such a finding was also confirmed by the similarity comparison of two LPS subtypes to the transcriptome of stromal vascular fraction at different differentiation stages. Transcriptomic analysis also demonstrated that metabolic pathways including the pentose phosphate pathway (PPP) were upregulated in WDLPS compared to DDLPS. Therefore, the cell line LPS853 was treated with the PPP inhibitor 6-aminonicotinamide ex vivo and the proliferation and invasion of LPS853 was significantly promoted by PPP inhibition, suggesting the potential role of PPP in the development and differentiation of LPS. In conclusion, this study described the altered lipid profiles of WDLPS and DDLPS for the first time, revealing the different differentiation stages of the two subtypes and providing a potential metabolic target for LPS treatment