A nomogram based on CT intratumoral and peritumoral radiomics features preoperatively predicts poorly differentiated invasive pulmonary adenocarcinoma manifesting as subsolid or solid lesions: a double-center study

BackgroundThe novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models’ generalization ability.MethodsWe retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance.ResultsThe AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05).ConclusionThe nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively

Trajectory Optimization for High-Speed and Long-Range Interceptor Based on Improved Adaptive hp Pseudospectral Method

The trajectory optimization design of interceptor is very important in the defense combat against a class of high-speed and strong-maneuvering aircraft. At present, an important idea is to use hp pseudospectral method to offline optimizes the trajectory of interceptor, but the solving efficiency of this method needs to be further improved. Aiming at this issue, an improved adaptive hp pseudospectral method is proposed in this paper. In order to shorten the solving time of the algorithm, the proposed method has two main improvements on the basis of the traditional hp pseudospectral method: on one hand, by judging the positions of the control sudden change points, prerefine the mesh around them according to certain rules. On the other hand, the curvature of the system state curve is used as the criterion to segment the original mesh nonuniformly so that more mesh points can be allocated where the curvature is large. These two points together ensure that the collocation point resources can be used more efficiently in the mesh refinement process. The simulation results show that the proposed method can solve the optimized trajectory of interceptor effectively, and it also proves that this method has higher solving efficiency than the traditional adaptive hp method

An Improved Predictor-Corrector Guidance Algorithm for Reentry Glide Vehicle Based on Intelligent Flight Range Prediction and Adaptive Crossrange Corridor

For traditional predictor-corrector guidance algorithm for reentry glide vehicle, it cost a lot of time to obtain predicted flight range with a slow speed to iterate. In this paper, according to residual network (ResNet)’s block and dynamic model of vehicle, through analyzing the characteristics of predicted flight range with constraints, the flight range prediction block and flight range prediction neural network are designed, which can obtain the predicted range accurately and quickly; then aiming at the separation between guidance logic and no-fly zone avoidance logic, which may lead to guidance failure and increasing of the sign variation number of the bank angle, the no-fly zone crossrange and the no-fly zone mapping crossrange are proposed in this paper. According the repulsion force of artificial potential field, an adaptive crossrange corridor combining guidance logic and no-fly zone avoidance logic is proposed, and the convergence of the corridor is analyzed theoretically. Through simulation, the block number of flight range prediction network is determined firstly. By this method, the efficiency of lateral guidance can be improved. Then, through the simulation with the different no-fly zones under different disturbed conditions, the stability and validity of the guidance method are verified. Finally, compared with other predictor-corrector algorithms, the proposed method can realize guidance with less sign variation number of bank angle and better avoidance for no-fly zones

Distribution of branched glycerol dialkyl glycerol tetraethers in soils on the Northeastern Qinghai-Tibetan Plateau and possible production by nitrite-reducing bacteria

Branched glycerol dialkyl glycerol tetraethers (bGDGTs) are ubiquitous and abundant in soils, but their sources remain elusive. Recent studies demonstrate that the distributions of bGDGTs are sensitive to various environmental factors. In an effort to understand how and to what extent soil moisture (expressed as soil water content (SWC) or mean annual precipitation (MAP), pH and temperature may impact the distribution of bGDGTs, and to shed more light on the biological sources of bGDGTs in cold and arid regions, we investigated the distribution of bGDGTs as well as bacterial 16S rRNA gene and functional genes involved in the N cycle (including amoA, nirS and nirK) in 41 surface soil samples from around Lake Qinghai and east of Qaidam Basin on the Northeastern Qinghai-Tibetan Plateau. We found that lower soil moisture reduced the fractional concentrations of cyclic bGDGTs and thus the cyclisation ratio of branched tetraethers (CBT) index correlated negatively with SWC and MAP, suggesting that soil moisture is an important factor controlling bGDGT distributions in soils in this arid and semi-arid region. Two subgroups of bGDGTs were assigned on the basis of cluster analysis, and bGDGT indices behaved differently in the two groups, hinting at different biosynthetic mechanisms for bGDGTs under different environmental conditions. Real time PCR results showed that nirS and nirK genes correlated significantly with the concentration of bGDGTs, suggesting that the nirS- or nirK-encoding bacteria involved in denitrification might potentially be an additional biological source for soil bGDGTs (besides Acidobacteria). Moreover, our results also support the application of new indices based on 5-methyl bGDGTs and 6-methyl bGDGTs in reconstructing past temperature and pH variations in this region

A Trajectory Generation Algorithm for a Re-Entry Gliding Vehicle Based on Convex Optimization in the Flight Range Domain and Distributed Grid Points Adjustment

Optimal trajectory generation for the guidance of re-entry glide vehicles is of great significance. To realize a faster generation speed and consistency with the guidance mechanism, an improved convex optimization trajectory generation algorithm based on the flight range domain for the re-entry glide vehicles is proposed in this paper. Firstly, according to the definition of the range-to-go, the projected range-to-go of the re-entry glide vehicle is presented when the dynamic model is converted to the flight range domain. Then, the attack angle and bank angle are expanded to the state variables and the change rate, which is designed as a new control variable. When the dynamic models and constraints are convexificated and discretized, the vehicle trajectory discrete convex model in the flight range domain is proposed. In order to further improve the generation speed and accuracy, an initial trajectory generation method that is close to the guidance requirements is proposed by the landing points of different control laws. In addition, by analyzing the nonlinear illegal degree of grid points, the probability density of grid points and the adjustment strategy of grid points are proposed. Finally, the ablation experiment shows that the initial trajectory generation and distributed grid points method works. With different target points, different no-fly zones, different initial states, and the Monte Carlo experiment, our method can effectively and robustly complete the generation. The lateral and longitudinal generation error is less than 1 km. And compared with the Gaussian pseudo-spectral method, our method obtained comparable accuracy and faster speed

Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies

Antiviral drugs have benefited public health officers to elucidate outbreak risks by controlling influenza pandemics efficacious, especially effective in the early stage of epidemic outbreaks. To limit explosive strain on hospitals, commercial pharmacies have joined, as antiviral drug-dispensing partners, in governments’ pandemic response plans. Existing researches focus on site selection by optimizing the single objective of access to the target population. However, there are substantial inevitable but essential social factors (such as social unbalance, spatial unbalance and resource unbalance) needed to consider to benefit the society best. In this paper, we propose a network-perspective optimization model across multiple social scales (e.g, access, social unbalance, spatial unbalance and resource unbalance) to assign antiviral drugs to the urban dispensing pharmacies. In the network-based frame, we transfer these considerations to the constraints of group, edge, and node. The constrained optimization model is studied and solved using methods of willingness-to-travel model, L12 norm and network lasso, corresponding to each considerations. Taking Shanghai in a cohort of 11 million individuals as an example, we have shown the flexibility of the proposed multi-objective model, comparing with the traditional methods. For example, we found that there are 29 pharmacies needed with covering 81% districts by tradition single-objective method. In the contrast, only 12 pharmacies are needed with similar access ability but can still cover 75% districts. Or more pharmacies are assigned with covering 87% districts. This research can supply an initial exploration of pharmacy-based distribution of antiviral drugs for the studying construction of strategic national stockpile in some countries