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Aiming at the problem of feature extraction and recognition in high resolution range profile (IIRRP) target recognition, a recognition method based on one-dimensional stacked pooling fusion convolutional autoencoder (ID SPF-CAE) is proposed in this paper. Firstly, a one-dimensional pooling fusion convolutional autoencoder (ID PF-CAE) is constructed. In the encoding stage, the maximum pooling and average pooling are used to extract different encoding features and fuse them to extract the structural features of IIRRP. Then, multiple ID PF-CAEs are stacked to form ID SPF-CAE. Finally, the network is fine-tuned using label data to realize IIRRP target recognition. And the AdaBound algorithm is used to optimize network training for improving the recognition performance. The experimental results based on the simulated data of the target in the middle part of the trajectory show that the method has strong feature extraction capability, and has high accuracy and robustness for IIRRP target recognition. [ABSTRACT FROM AUTHOR]

To solve the problem of midcourse ballistic target recognition, the existing recognition methods based on high resolution range profile (HRRP) directly extract the overall features of 1-dimension HRRP (1D-HRRP), which has a weak ability to extract local features, and the expression ability of features extracted from 1D-HRRP is limited. Therefore, a recognition method for midcourse ballistic targets of HRRP images based on the deep convolutional neural network (DCNN) is proposed. Firstly, 1D-HRRP is transformed into 0 -- 1 binary images, so that the numerical variation features are transformed into the graph structure features. Then, DCNN is constructed to extract the local and common features of HRRP images layer by layer and recognize them. Finally, Dropout and L2 regularization are combined to alleviate the over-fitting problem of DCNN, and AdaBound algorithm is used to improve the convergence speed and accuracy of DCNN training. The experimental results show that the recognition method based on HRRP images is more accurate than other 12 recognition methods based on 1D-HRRP or 2-dimension HRRP (2D-HRRP), and achieves an accuracy of 96.28% in the test dataset, verifying the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The coupling reaction of substituted toluenes themselves and the cross-coupling reaction of substituted toluene and aromatic in the presence of bromine in anhydrous CCl4 under irradiation lead to diphenylmethanes with moderate to good yields. The methylene moiety in diphenylmethanes comes from the toluene with fewer electron-donating groups, and regioselectivity was observed. [ABSTRACT FROM AUTHOR]

Three‐photon microscopy excited at the 1700‐nm window enables deep‐tissue penetration. However, the refractive indices of commonly used immersion oils, and the resultant pulse broadening are not known, preventing imaging optimization. Here, we demonstrate detailed characterization of the refractive index, pulse broadening and distortion for excitation pulses at this window for commonly used immersion oils. On the physical side, we uncover that absorption, rather than material dispersion, is the main cause of pulse broadening and distortion. On the application side, comparative three‐photon imaging results indicate that 1600‐nm excitation yields 5 times higher three‐photon signal than 1690‐nm excitation. This study demonstrates detailed characterization of wavelength‐dependent refractive index, pulse broadening, and absorption of immersion oils at the 1700‐nm window. From these results and the previously reported characterization of H2O and D2O, optimal immersion medium selection can be made for multiphoton microscopy of biological samples excited at this window. Comparative imaging of mouse skull using excitation wavelengths within the 1700‐nm window further demonstrates the applicability of these measurements. [ABSTRACT FROM AUTHOR]

Biodiesel has gained significant attention as an alternative to petroleum diesel. Currently, there is an increasing interest in obtaining microbial oils from oleaginous micro-organisms for biodiesel production. In the accumulation of microbial oils, carbon substrate constitutes a major portion of the cost. Accordingly, significant efforts have been made to explore suitable carbon sources, and to investigate their effects on cell growth as well as lipid synthesis. This paper reviews the current trend of using various carbon sources for microbial oils production, including carbon dioxide, conventional saccharides, energy crops, C2 compounds, lignocellulosic biomass, and glycerol. The strategies for enhancement of microbial oils production are further discussed. Finally, the constraints and perspectives of using microbial oils for biodiesel production are also highlighted. © 2012 Society of Chemical Industry and John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

BACKGROUND Wünderlich syndrome (WS) is a rare diagnosis of nontraumatic spontaneous renal hemorrhage into the subcapsular, perirenal, or pararenal spaces. Prompt and effective intervention is necessary for an accurate pathological diagnosis and preservation of life. In the current literature, open surgery is the primary option when conservative treatment fails, but there can be serious trauma and corresponding consequences. Herein, we present 3 cases of Wünderlich syndrome managed by robot-assisted laparoscopic nephrectomy via a retroperitoneal approach. CASE REPORT Patient 1 was a 44-year-old woman with right flank pain for 6 h. Patient 2 was a 53-year-old woman with a history of diabetes who had pain in her right flank pain and nausea for 1 day. Patient 3 was a 45-year-old man with left flank pain for 1 day. All cases of WS were confirmed by CT. All 3 patients were treated with retroperitoneal robot-assisted nephrectomy after conservative treatment failed. Pathological examination confirmed that patient 1 had angiomyolipoma, and patients 2 and 3 had renal clear cell carcinoma. At the 9-month follow-up, renal function was good and no evidence of recurrence or metastasis has been detected. CONCLUSIONS These cases have highlighted the importance of the clinical history and imaging findings in the diagnosis of Wünderlich syndrome, and show that rapid management can be achieved using robot-assisted laparoscopic nephrectomy. However, it is crucial to have a skilled surgical team and adequate preoperative preparation.

The toxicity of lead presents a critical challenge for the application of perovskite optoelectronics. Lead-free perovskite solar cells were achieved with formamidinium tin iodide (FASnI 3 ) perovskites, exhibiting decent power-conversion efficiencies (PCEs) of up to 14%, with >98% of the initial PCE retained after 3000 h of storage. However, when employed in light-emitting applications, FASnI 3 -based perovskite LEDs (PeLEDs) show limited stability, with T 50 lifetimes of up to 0.25 h at 10 mA cm -2 . Here, we improve the stability of FASnI 3 -based PeLEDs through the inclusion of a two-dimensional precursor phenethylamine iodide (PEAI), allowing controlled crystallization of the mixed-dimensional perovskite emitters. The density of defects is found to be reduced, accompanied by the suppression of oxidation from Sn 2+ to Sn 4+ . Using an optimized perovskite composition, we achieve an EQE of 1.5% (a ∼10-fold improvement over the control devices), a maximum radiance of 145 W sr -1 m -2 , and a record-long T 50 lifetime of 10.3 h at 100 mA cm -2 for FASnI 3 -based PeLEDs. Our results illuminate an alternative path toward lead-free PeLED applications.

Epithelial ovarian cancer (EOC) prognosis is associated with International Federation of Gynecology and Obstetrics (FIGO) staging, cancer cell classification, patient age, and residual tumor size. However, the molecular markers for predicting EOC prognosis remain to be explored. In this study, we investigated the expression of CD24, COX-2, and p53 in EOC, and their relationships to clinical prognosis. We found that the expression of CD24 was detected in the cell membrane in 90.6 percent (58/64) of EOC cases and in the cytoplasm in 54.7 percent (35/64) of EOC cases; 78.6 percent (11/14) cases of borderline tumors had CD24-positive staining in the cell membrane. All 9 cases of benign tumors were negative for CD24 staining. Expression of CD24 correlated with the nuclear expression of p53, but not with the expression of COX-2. Overexpression of CD24 is an independent factor associated with tumor metastasis, a low survival rate, and a short survival time. Our results suggest that CD24 may be a valuable molecular marker for predicting prognoses of patients with EOC.

Objective: Investigate the frequency of loss of heterozygosity (LOH) at chromosome arm the short arm chromosome 3p14, 25 in the serum DNA from ovarian cancer and its clinical application., Methods: Thirty-eight ovarian cancer serum samples with 18 corresponding tumor tissues and 8 benign ovarian tumors were obtained, and DNA samples extracted from serum and tissue were examined for 3p14, 25 LOH by using of polymerase chain reaction with four polymorphic microsatellite markers (D3S1029, D3S1228, D3S1300, D3S1481)., Results: Matched serum and tissue DNAs from 18 ovarian cancer patients showed significant concordance of 3p14, 25 LOH (P < 0.05). 3p14, 25 LOH in at least one of four loci occurred in 29 out of 38 (76%) serum samples, while 17 serum samples (45%) exhibited LOH at more than one locus. According to International Federation of Gynecology and Obstetrics (FIGO) staging, there was a trend that the rate of LOH was higher in advanced stages, and the frequency of loss in stage II, III, IV was 2/4, 78%, 8/9 respectively. It was also found that the number of microsatellite markers with 3p14, 25 LOH was increased with tumor progressed. No significant association of pathological types with LOH in serum DNA could be demonstrated except at locus D3S1029., Conclusions: Since the strong correlation of 3p14, 25 LOH between serum DNA and tumor tissue DNA, as well as the frequency of 3p14, 25 LOH associated with malignancy of ovarian cancer, it is suggested that detection of serum DNA 3p14, 25 LOH may be used as a molecular marker for staging and monitoring human ovarian cancer.