Genetic Algorithm and Greedy Strategy-Based Multi-Mission-Point Route Planning for Heavy-Duty Semi-Rigid Airship.

The large volume and windward area of the heavy-duty semi-rigid airship (HSA) result in a large turning radius when the HSA passes through every mission point. In this study, a multi-mission-point route planning method for HSA based on the genetic algorithm and greedy strategy is proposed to direct the HSA maneuver through every mission point along the optimal route. Firstly, according to the minimum flight speed and the maximum turning slope angle of the HSA during turning, the minimum turning radius of the HSA near each mission point is determined. Secondly, the genetic algorithm is used to determine the optimal flight sequence of the HSA from the take-off point through all the mission points to the landing point. Thirdly, based on the optimal flight sequence, the shortest route between every two adjacent mission points is obtained by using the route planning method based on the greedy strategy. By determining the optimal flight sequence and the shortest route, the optimal route for the HSA to pass through all mission points can be obtained. The experimental results show that the method proposed in this study can generate the optimal route with various conditions of the mission points using simulation studies. This method reduces the total voyage distance of the optimal route by 18.60% on average and improves the flight efficiency of the HSA.

The metagenomic next-generation sequencing in diagnosing central nervous system angiostrongyliasis: a case report.

BACKGROUNDS: The incidence of angiostrongyliasis is increasing in recent decades due to the expanding endemic areas all over the world. Clinicians face tremendous challenge of diagnosing angiostrongyliasis because of the lack of awareness of the disease and less effective definitive laboratory tests. CASE PRESENTATION: A 27-year-old man initially manifested skin itching, emesis, myalgia and quadriparesis. With progressive weakness of four limbs and elevated protein in the cerebrospinal fluid (CSF), he was diagnosed as Guillain-Barré syndrome and treated with intravenous methylprednisolone and immunoglobulin. However, the patient deteriorated with hyperpyrexia, headache and then persistent coma. The routine tests for Angiostrongylus cantonensis (A. cantonensis) with both the CSF and the serum were all negative. In contrast, the metagenomic next-generation sequencing (mNGS) was applied with the serum sample and the CSF sample in the middle phase. The central nervous system (CNS) angiostrongyliasis was diagnosed by mNGS with the mid-phase CSF, but not the mid-phase serum. At the same time, the CSF analysis revealed eosinophils ratio up to 67%. The discovery of A. cantonensis was confirmed by PCR with CSF later. Unfortunately, the patient died of severe angiostrongyliasis. During his hospitalization, mNGS was carried out repeatedly after definitive diagnosis and targeted treatment. The DNA strictly map reads number of A. cantonensis detected by mNGS was positively correlated with the CSF opening pressure and clinical manifestations. CONCLUSIONS: The case of A. cantonensis infection highlights the benefit of mNGS as a target-free identification in disclosing the rare CNS angiostrongyliasis in the unusual season, while solid evidence from routine clinical testing was absent. The appropriate sample of mNGS should be chosen according to the life cycle of A. cantonensis. Besides, given the fact that the DNA reads number of A. cantonensis fluctuated with CSF opening pressure and clinical manifestations, whether mNGS could be applied as a marker of effectiveness of treatment is worth further exploration.

Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image.

Tilting sampling is a novel sampling mode for achieving a higher resolution of hyperspectral imagery. However, most studies on the tilting image have only focused on a single band, which loses the features of hyperspectral imagery. This study focuses on the restoration of tilting hyperspectral imagery and the practicality of its results. First, we reduced the huge data of tilting hyperspectral imagery by the p-value sparse matrix band selection method (pSMBS). Then, we restored the reduced imagery by optimal reciprocal cell combined modulation transfer function (MTF) method. Next, we built the relationship between the restored tilting image and the original normal image. We employed the least square method to solve the calibration equation for each band. Finally, the calibrated tilting image and original normal image were both classified by the unsupervised classification method (K-means) to confirm the practicality of calibrated tilting images in remote sensing applications. The results of classification demonstrate the optimal reciprocal cell combined MTF method can effectively restore the tilting image and the calibrated tiling image can be used in remote sensing applications. The restored and calibrated tilting image has a higher resolution and better spectral fidelity.

Continuous-Time Laser Frames Associating and Mapping via Multilayer Optimization.

To achieve the ability of associating continuous-time laser frames is of vital importance but challenging for hand-held or backpack simultaneous localization and mapping (SLAM). In this study, the complex associating and mapping problem is investigated and modeled as a multilayer optimization problem to realize low drift localization and point cloud map reconstruction without the assistance of the GNSS/INS navigation systems. 3D point clouds are aligned among consecutive frames, submaps, and closed-loop frames using the normal distributions transform (NDT) algorithm and the iterative closest point (ICP) algorithm. The ground points are extracted automatically, while the non-ground points are automatically segmented to different point clusters with some noise point clusters omitted before 3D point clouds are aligned. Through the three levels of interframe association, submap matching and closed-loop optimization, the continuous-time laser frames can be accurately associated to guarantee the consistency of 3D point cloud map. Finally, the proposed method was evaluated in different scenarios, the experimental results showed that the proposed method could not only achieve accurate mapping even in the complex scenes, but also successfully handle sparse laser frames well, which is critical for the scanners such as the new Velodyne VLP-16 scanner's performance.

MFG-E8 reverses microglial-induced neurotoxic astrocyte (A1) via NF-κB and PI3K-Akt pathways.

Recent evidence have suggested that neuroinflammation and ischemia induce the activation of two different types of reactive astrocytes, termed A1 and A2. Additionally, A1 astrocytes contribute to the death of neurons and oligodendrocytes in neurodegenerative diseases, such as Alzheimer's disease (AD). In the current study, we constructed an Aß42-activated microglia-conditioned medium to induce A1 astrocytic activation via secretion of interleukin 1α, tumor necrosis factor, and complement component 1q in vitro, and indicated the regulatory role of milk fat globule epidermal growth factor 8 (MFG-E8) on A1/A2 astrocytic alteration through the downregulation of nuclear factor-κB and the upregulation of PI3K-Akt. This study showed that MFG-E8 suppressed A1 astrocytes and holds great potential for the treatment of AD.

Hyperspectral Imagery Super-Resolution by Adaptive POCS and Blur Metric.

The spatial resolution of a hyperspectral image is often coarse as the limitations on the imaging hardware. A novel super-resolution reconstruction algorithm for hyperspectral imagery (HSI) via adaptive projection onto convex sets and image blur metric (APOCS-BM) is proposed in this paper to solve these problems. Firstly, a no-reference image blur metric assessment method based on Gabor wavelet transform is utilized to obtain the blur metric of the low-resolution (LR) image. Then, the bound used in the APOCS is automatically calculated via LR image blur metric. Finally, the high-resolution (HR) image is reconstructed by the APOCS method. With the contribution of APOCS and image blur metric, the fixed bound problem in POCS is solved, and the image blur information is utilized during the reconstruction of HR image, which effectively enhances the spatial-spectral information and improves the reconstruction accuracy. The experimental results for the PaviaU, PaviaC and Jinyin Tan datasets indicate that the proposed method not only enhances the spatial resolution, but also preserves HSI spectral information well.

The association between brain-derived neurotrophic factor gene polymorphism and migraine: a meta-analysis.

BACKGROUND: Migraine is a recurrent headache disease related to genetic variants. The brain-derived neurotrophic factor (BDNF) gene rs6265 (Val66Met) and rs2049046 polymorphism has been found to be associated with migraine. However, their roles in this disorder are not well established. Then we conduct this meta-analysis to address this issue. METHODS: PubMed, Web of Science and Cochrane databases were systematically searched to identify all relevant studies. Odds ratio (OR) with corresponding 95% confidence interval (CI) was used to estimate the strength of association between BDNF gene rs6265 and rs2049046 polymorphism and migraine. RESULTS: Four studies with 1598 cases and 1585 controls, fulfilling the inclusion criteria were included in our meta-analysis. Overall data showed significant association between rs6265 polymorphism and migraine in allele model (OR = 0.86, 95%CI: 0.76-0.99, p = 0.03), recessive model (OR = 0.84, 95%CI: 0.72-0.98, p = 0.03) and additive model (GG vs GA: OR = 0.85, 95%CI: 0.72-1.00, p = 0.04), respectively. We also found significant association between rs2049046(A/T) polymorphism and migraine in allele model (OR = 0.88, 95%CI: 0.79-0.98, p = 0.02), recessive model (OR = 0.80, 95%CI: 0.67-0.96, p = 0.02) and additive model (AA vs TT: OR = 0.72, 95%CI: 0.57-0.92, p = 0.008; AA vs AT: OR = 0.81, 95%CI: 0.67-0.99, p = 0.03), respectively. CONCLUSION: Our meta-analysis suggested that BDNF rs6265 and rs2049046 polymorphism were associated with common migraine in Caucasian population. Further studies are awaited to update this finding in Asian population and other types of migraine.

Relationship between visible branch arteries distal to the stenosis on magnetic resonance angiography and stroke recurrence in patients with severe middle cerebral artery trunk stenosis: a one-year follow up study.

BACKGROUND: To evaluate the relationship between the flow signal intensity of branch arteries distal to the stenosis on 3-dimensional (3D) time-of-flight (TOF) magnetic resonance angiography (MRA) and the risk of stroke recurrence in patients with severe middle cerebral artery (MCA) trunk stenosis. METHODS: We prospectively recruited 153 patients (mean age 62.9 ± 13.0 years, 106 males) with a first ischemic stroke or transient ischemic attack caused by a severe MCA trunk stenosis (70 % to 99 %) confirmed by 3D TOF MRA and followed them for one year to determine the stroke recurrence. The MCA branch signal intensity distal to the site of stenosis on 3D TOF MRA was classified as either good (grade A) or poor [mild reduction (grade B) or severe reduction (grade C)] according to the extent to which the MCA could be visualized. The patients were divided into groups A (35), B (58), or C (60) based on the MRA grading of the MCA branch signal intensity distal to the site of stenosis. RESULTS: Poor MCA branch signal intensity was associated with internal border-zone infarction (p < 0.05). The risk of stroke recurrence in the ipsilateral MCA in the first year was 18.3 %. The 1-year cumulative incidence of recurrence was higher in the patients in group C (30 %) than in groups B (12.1 %) or A (8.6 %) (Log rank, p = 0.007). Multivariate analyses via Cox proportional hazard regression demonstrated that only a grade C classification of the signal intensity of the MCA branches was an independent predictor of stroke recurrence in the ipsilateral MCA (hazard ratio = 3.0, 95 % confidence interval = 1.3-7.4, p = 0.014). CONCLUSIONS: This study demonstrated that MCA branch signal intensity as assessed via 3D TOF MRA may be a useful and simple tool to stratify the risk of stroke recurrence in patients with severe MCA trunk stenosis.

A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters.

This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.

Optimization Algorithm for Kalman Filter Exploiting the Numerical Characteristics of SINS/GPS Integrated Navigation Systems.

Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted "useful" data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency.

Intracranial versus Extracranial Symptomatic Carotid Atherosclerosis in Chinese Patients: Risk Factors, Stroke Mechanisms, and Long-Term Prognosis.

OBJECTIVES: This study aims to investigate the clinical-radiological features and stroke mechanisms of symptomatic intracranial internal carotid artery (IICA) atherosclerosis and prognoses of patients with IICA atherosclosis, and compare these data with those from patients with symptomatic extranial carotid artery (EICA) atherosclerosis. METHODS: We prospectively recruited 155 patients with symptomatic IICA or EICA atherosclerosis (stenosis ≥50% or occlusion) from 1968 Chinese patients with a first-ever ischemic stroke or transient ischemic attack. The patients were followed up for stroke recurrence, cardiovascular events, and death. RESULTS: There were 80 and 75 patients in the IICA and EICA groups, respectively. Multivariate logistic regression analyses showed that the patients in the IICA group were associated with hypertension (odds ratio [OR], 5.980; 95% confidence interval [CI], 1.790-19.976) and asymptomatic intracranial atherosclerosis (OR, 2.564; 95% CI, 1.222-5.377), while the patients in the EICA group were associated with smoking (OR, 2.397; 95% CI, 1.150-4.998) and contralateral EICA disease (OR, 4.742; 95% CI, 1.455-15.455). Hemodynamic stroke alone was more common in the IICA group; artery-to-artery embolism was identified more often in the EICA group (P <.05). The cumulative incidences of ipsilateral stroke recurrence, stroke recurrence and cardiovascular events, and death at 5 years were 43.5%, 52.4%, and 27.3%, respectively, in the patients of the IICA group, which did not differ from those of the EICA group. CONCLUSIONS: IICA atherosclerosis as well as EICA atherosclerosis is an important cause of stroke in Chinese patients. Patients with symptomatic IICA atherosclerosis had unique clinical-radiological features and stroke mechanisms compared with those with symptomatic EICA atherosclerosis; their long-term prognosis was poor.

Intracranial versus extracranial artery dissection cases presenting with ischemic stroke.

BACKGROUND: To compare the clinical and radiologic characteristics, possible stroke mechanisms, and prognosis of intracranial artery dissections (IADs) with those of extracranial artery dissections (EADs) presenting with cerebral infarction. METHODS: Among 3250 adult patients with acute ischemic stroke (cerebral infarction), we prospectively recruited and categorized patients with cerebral infarction secondary to spontaneous cerebral artery dissection into IAD or EAD groups. The clinical and radiologic characteristics, possible stroke mechanisms according to the distributions of the infarctions based on diffusion-weighted imaging, and prognosis were analyzed for both groups. RESULTS: There were 48 and 50 patients experiencing IAD and EAD, accounting for 1.5% and 1.5% of all ischemic stroke patients, respectively. Compression of the perforating artery was the most common possible stroke mechanism (33.3%) in IADs; thromboembolism was more common in EADs than that in IADs (36 of 50 versus 12 of 48; P < .001). Magnetic resonance imaging and angiography were used to investigate the arterial dissections in all IAD patients and 46 EAD patients. Based on magnetic resonance imaging and angiography, the IADs more frequently displayed dissecting aneurysm (6 of 48 versus 0 of 46; P = .027) and intimal flap or double lumen (21 of 48 versus 4 of 46; P < .001) than EADs. For the clinical characteristics and prognosis, there was no significant difference between the 2 groups. CONCLUSIONS: These results indicate that IAD is an important cause of ischemic stroke, and it displays unique radiologic characteristics and specific stroke mechanisms compared with EAD.

[Hyperspectral Band Selection Based on Spectral Clustering and Inter-Class Separability Factor].

With the development of remote sensing technology and imaging spectrometer, the resolution of hyperspectral remote sensing image has been continually improved, its vast amount of data not only improves the ability of the remote sensing detection but also brings great difficulties for analyzing and processing at the same time. Band selection of hyperspectral imagery can effectively reduce data redundancy and improve classification accuracy and efficiency. So how to select the optimum band combination from hundreds of bands of hyperspectral images is a key issue. In order to solve these problems, we use spectral clustering algorithm based on graph theory. Firstly, taking of the original hyperspectral image bands as data points to be clustered , mutual information between every two bands is calculated to generate the similarity matrix. Then according to the graph partition theory, spectral decomposition of the non-normalized Laplacian matrix generated by the similarity matrix is used to get the clusters, which the similarity between is small and the similarity within is large. In order to achieve the purpose of dimensionality reduction, the inter-class separability factor of feature types on each band is calculated, which is as the reference index to choose the representative bands in the clusters furthermore. Finally, the support vector machine and minimum distance classification methods are employed to classify the hyperspectral image after band selection. The method in this paper is different from the traditional unsupervised clustering method, we employ spectral clustering algorithm based on graph theory and compute the interclass separability factor based on a priori knowledge to select bands. Comparing with traditional adaptive band selection algorithm and band index based on automatically subspace divided algorithm, the two sets of experiments results show that the overall accuracy of SVM is about 94. 08% and 94. 24% and the overall accuracy of MDC is about 87. 98% and 89. 09%, when the band selection achieves a relatively optimal number of clusters using the method propoesd in this paper. It effectively remains spectral information and improves the classification accuracy.

[The linear hyperspectral camera rotating scan imaging geometric correction based on the precise spectral sampling].

As the rotation speed of ground based hyperspectral imaging system is too fast in the image collection process, which exceeds the speed limitation, there is data missed in the rectified image, it shows as the_black lines. At the same time, there is serious distortion in the collected raw images, which effects the feature information classification and identification. To solve these problems, in this paper, we introduce the each component of the ground based hyperspectral imaging system at first, and give the general process of data collection. The rotation speed is controlled in data collection process, according to the image cover area of each frame and the image collection speed of the ground based hyperspectral imaging system, And then the spatial orientation model is deduced in detail combining with the star scanning angle, stop scanning angle and the minimum distance between the sensor and the scanned object etc. The oriented image is divided into grids and resampled with new spectral. The general flow of distortion image corrected is presented in this paper. Since the image spatial resolution is different between the adjacent frames, and in order to keep the highest image resolution of corrected image, the minimum ground sampling distance is employed as the grid unit to divide the geo-referenced image. Taking the spectral distortion into account caused by direct sampling method when the new uniform grids and the old uneven grids are superimposed to take the pixel value, the precise spectral sampling method based on the position distribution is proposed. The distortion image collected in Lao Si Cheng ruin which is in the Zhang Jiajie town Hunan province is corrected through the algorithm proposed on above. The features keep the original geometric characteristics. It verifies the validity of the algorithm. And we extract the spectral of different features to compute the correlation coefficient. The results show that the improved spectral sampling method is better than the direct sampling method. It provides the reference for the similar product used on the ground.

A satisfaction survey of current medicines used for migraine therapy in China: is Chinese patent medicine effective compared with Western medicine for the acute treatment of migraine?

OBJECTIVE: To investigate the patient satisfaction with medications commonly used for migraine therapy in patients seen in headache clinic in China with emphasis on the evaluation of Chinese patent medicine (CPM) in relieving acute migraine attack. METHODS: Patients admitted at headache clinics in the neurological departments of four hospitals during April to October 2011 were enrolled in the investigation. The questionnaire was designed based on the validation of a diagnostic questionnaire for a population-based survey in China in 2009. RESULTS: Among 219 eligible patients, 58% had used CPM at the acute attack of migraine while the guideline-recommended treatments were seldom used. However, patients using CPMs were less satisfied than those using Western Medicines (WMs) in either single medication groups or mixed medication groups (P < 0.05). CONCLUSION: Fifty-eight percent of the eligible respondents in Guangdong and Guangxi Province had used CPM at the acute attack of migraine, but based on our data, the effect of CPM on treating migraine attack was poor with low satisfaction compared with WMs. However, many factors may bias or explain our findings. This suggests the need for accelerated research in understanding patient choice, treatment availability, and use of medications.

[The hyperspectral camera side-scan geometric imaging in any direction considering the spectral mixing].

In order to correct the image distortion in the hyperspectral camera side-scan geometric Imaging, the image pixel geo-referenced algorithm was deduced in detail in the present paper, which is suitable to the linear push-broom camera side-scan imaging on the ground in any direction. It takes the orientation of objects in the navigation coordinates system into account. Combined with the ground sampling distance of geo-referenced image and the area of push broom imaging, the general process of geo-referenced image divided into grids is also presented. The new image rows and columns will be got through the geo-referenced image area dividing the ground sampling distance. Considering the error produced by round rule in the pixel grids generated progress, and the spectral mixing problem caused by traditional direct spectral sampling method in the process of image correction, the improved spectral sampling method based on the weighted fusion method was proposed. It takes the area proportion of adjacent pixels in the new generated pixel as coefficient and then the coefficients are normalized to avoid the spectral overflow. So the new generated pixel is combined with the geo-referenced adjacent pixels spectral. Finally the amounts of push-broom imaging experiments were taken on the ground, and the distortion images were corrected according to the algorithm proposed above. The results show that the linear image distortion correction algorithm is valid and robust. At the same time, multiple samples were selected in the corrected images to verify the spectral data. The results indicate that the improved spectral sampling method is better than the direct spectral sampling algorithm. It provides reference for the application of similar productions on the ground.

Thymol improves the growth performance of blue foxes by regulating the gut microbiota.

Introduction: The drawbacks of using antibiotics as feed additives for blue foxes have gradually become apparent; moreover, thymol has wide-spectrum antimicrobial activity and has the potential to replace antibiotics in various animals. However, there are few reports on the effects of thymol on blue foxes. Methods: This study aimed to investigate the effects of different concentrations of thymol on the growth performance, apparent nutrient digestibility, serum biochemical indicators, intestinal morphology, and gut microbiota of blue foxes. Twenty-four male blue foxes (120 ± 5 d) of similar weight (6.05 ± 0.16 kg) were randomly divided into 4 groups. 0, 100, 200, and 300 mg/kg thymol were added to the basal diets of groups C, L, M, and H, respectively. Results: Compared with those in the C group, the addition of 100 mg/kg thymol to the diet significantly increased organic matter (OM) digestibility, crude protein (CP) digestibility, immunoglobulin (Ig) A, IgM, the VH of the duodenum, the CD of the jejunum, the VH of the ileum, and the VH/CD of the ileum (P < 0.05) and strongly significantly increased IgG (P < 0.01). The addition of 200 mg/kg thymol to the diet increased the VH/CD of the duodenum (P < 0.05). The addition of 300 mg/kg thymol to the diet significantly increased the VH and CD of the jejunum (P < 0.05). The addition of 200 mg/kg and 300 mg/kg thymol to the diets increased the final weight (FW) (P < 0.05). Adding 100 mg/kg thymol significantly increased the levels of interleukin-4 (IL-4) and catalase (CAT) compared with those in the other groups (P < 0.05). 16S rRNA gene detection revealed that thymol can change the abundances of Bifidobacterium, Fusobacterium, Allobaculum, Streptococcus, Megasphaera, and Lactobacillus in the gut. Conclusion: The addition of thymol to diets can increase the abundance of Bifidobacterium, Fusobacterium, and Allobaculum, which may contribute to improving the growth performance of blue foxes.

Prognostic Evaluation for Hepatocellular Carcinoma with Portal Vein Tumor Thrombus Patients Treated with Transarterial Chemoembolization Plus Molecular Targeted Therapies-Development and Validation of the ABPS Score.

RATIONALE AND OBJECTIVES: Transarterial chemoembolization (TACE) plus molecular targeted therapies has emerged as the main approach for treating hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT). A robust model for outcome prediction and risk stratification of recommended TACE plus molecular targeted therapies candidates is lacking. We aimed to develop an easy-to-use tool specifically for these patients. METHODS: A retrospective analysis was conducted on 384 patients with HCC and PVTT who underwent TACE plus molecular targeted therapies at 16 different institutions. We developed and validated a new prognostic score which called ABPS score. Additionally, an external validation was performed on data from 200 patients enrolled in a prospective cohort study. RESULTS: The ABPS score (ranging from 0 to 3 scores), which involves only Albumin-bilirubin (ALBI, grade 1: 0 score; grade 2: 1 score), PVTT(I-II type: 0 score; III-IV type: 1 score), and systemic-immune inflammation index (SII,<550 × 1012: 0 score; ≥550 × 1012: 1 score). Patients were categorized into three risk groups based on their ABPS score: ABPS-A, B, and C (scored 0, 1-2, and 3, respectively). The concordance index (C-index) of the ABPS scoring system was calculated to be 0.802, significantly outperforming the HAP score (0.758), 6-12 (0.712), Up to 7 (0.683), and ALBI (0.595) scoring systems (all P < 0.05). These research findings were further validated in the external validation cohorts. CONCLUSION: The ABPS score demonstrated a strong association with survival outcomes and radiological response in patients undergoing TACE plus molecular targeted therapy for HCC with PVTT. The ABPS scoring system could serve as a valuable tool to guide treatment selection for these patients.

[An improved low spectral distortion PCA fusion method].

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

Multi-index fuzzy comprehensive evaluation model with information entropy of alfalfa salt tolerance based on LiDAR data and hyperspectral image data.

Rapid, non-destructive and automated salt tolerance evaluation is particularly important for screening salt-tolerant germplasm of alfalfa. Traditional evaluation of salt tolerance is mostly based on phenotypic traits obtained by some broken ways, which is time-consuming and difficult to meet the needs of large-scale breeding screening. Therefore, this paper proposed a non-contact and non-destructive multi-index fuzzy comprehensive evaluation model for evaluating the salt tolerance of alfalfa from Light Detection and Ranging data (LiDAR) and HyperSpectral Image data (HSI). Firstly, the structural traits related to growth status were extracted from the LiDAR data of alfalfa, and the spectral traits representing the physical and chemical characteristics were extracted from HSI data. In this paper, these phenotypic traits obtained automatically by computation were called Computing Phenotypic Traits (CPT). Subsequently, the multi-index fuzzy evaluation system of alfalfa salt tolerance was constructed by CPT, and according to the fuzzy mathematics theory, a multi-index Fuzzy Comprehensive Evaluation model with information Entropy of alfalfa salt tolerance (FCE-E) was proposed, which comprehensively evaluated the salt tolerance of alfalfa from the aspects of growth structure, physiology and biochemistry. Finally, comparative experiments showed that: (1) The multi-index FCE-E model based on the CPT was proposed in this paper, which could find more salt-sensitive information than the evaluation method based on the measured Typical Phenotypic Traits (TPT) such as fresh weight, dry weight, water content and chlorophyll. The two evaluation results had 66.67% consistent results, indicating that the multi-index FCE-E model integrates more information about alfalfa and more comprehensive evaluation. (2) On the basis of the CPT, the results of the multi-index FCE-E method were basically consistent with those of Principal Component Analysis (PCA), indicating that the multi-index FCE-E model could accurately evaluate the salt tolerance of alfalfa. Three highly salt-tolerant alfalfa varieties and two highly salt-susceptible alfalfa varieties were screened by the multi-index FCE-E method. The multi-index FCE-E method provides a new method for non-contact non-destructive evaluation of salt tolerance of alfalfa.