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This letter designed a circularly polarized horn antenna by loading a frequency selective surface (FSS) polarization converter at the aperture of a standard horn. The proposed polarization converter is based on multilayer nonresonant FSS. It is composed of a two-layer dielectric slab and three printed metal layers, which are etched on the top, middle, and bottom layers of the slab. The three metal layers consist of a two-layer patch with a square truncated corner and a one-layer grid line with a slot. By introducing perturbation to both the patch and the grid line, the polarization converter shows a low profile and subwavelength unit size, whose dimension is 0.18 λ 0 × 0.18 λ 0 while the thickness is only 0.1 λ 0. The simulated results show that the axial ratio (AR) is less than 3 dB in the frequency range of 9.6–11.7 GHz, i.e., a fractional bandwidth of 19.7% within the targeted frequency band. The measurement results are in a good agreement with the simulation results, which proves the feasibility of the design.

This paper optimizes the parallel receiver algorithm, the parallel receiver system applies parallel demodulation algorithm and dynamic signal detection algorithm into modules such as data arrangement, FFT processing, and phase compensation. With the improved algorithm, parallel receiver can realize the accurate decision of the effective signal and demodulate the parallel signal quickly.

The number of vulnerabilities in modern IT systems is explosive growing. Security researchers spend a lot of time on the work of vulnerability reproduce. In this process, an important work is building the vulnerable environment. Traditional technologies have two problems: different vulnerability report format from different sources and lack of network devices simulation. We propose an automatic deliberated vulnerable environment generating framework with network devices simulation based on structured vulnerability intelligence. And we implemented a prototype system to demonstrate the framework.

Undesired physiological instability remains a major limitation for nanoparticle-based drug delivery. To overcome this issue, a dual pH-responsive supramolecular layer-crosslinked nanoparticles (PCB-b-PCD/PBM-b-PDPA NPs, PDM NPs), which consisted of pH-responsive hydrophobic poly(diisopropylethyl methacrylate) (pKa ≈6.3) as the core, hydrophilic poly((methacrylic acid betaine) methyl methacrylate) as the shell and pH-responsive supramolecular crosslinked layer based on β-cyclodextrin and benzimidazole (pKa

Human tumor cell lines, especially those with complete data and follow-up, are important tools in tumor biological studies. Clear cell renal cell cancer (ccRCC) is not sensitive to radiotherapy or chemotherapy, and treatment of patients with distant metastasis relies on targeted therapy. Here, we report the establishment of seven new ccRCC stable cell lines that were continuously cultured for more than 20 generations among 81 cases of renal cell cancer. Moreover, gene expression and methylation in the established cell lines, in those that had a finite in vitro life span of less than 10 generations, and in cells that originated from the same culture at different generations were profiled using microarrays. Genes including SLC34A2, SEPP1, SULT1C4 and others were differentially expressed in established cell lines and finite cell lines, and changes in their expression might be caused by methylation or demethylation. The expression level of SLC34A2 was related not only to the life span in vitro culture but also to tumor size. Additionally, six of the seven new ccRCC cell lines had VHL deletions or termination mutations. So in addition to the establishment of seven new ccRCC cell lines with complete clinical data, we conclude that genes such as SLC34A2 and VHL play key roles in the continuous in vitro growth and development of ccRCC.

A 26-GHz cylindrical Luneburg lens antenna loaded with printed metal loops for low side lobe level is proposed in this paper. The microwave generated by the feeding waveguide is focused in the E-plane. 6-shell technology is utilized for the lens design. In the H-plane, the lens functioned as a loading dielectric and thus a radiation pattern with high side lobe level occurs. Proposed printed loops affect the H-field distribution of the antenna and through the loops, radiation pattern in H-plane could be adjusted in certain degree. With suitable size for the loading loops, the side lobe level reduction of approximate −8.5 dB will be realized in the H-plane radiation pattern at 26 GHz for the cylindrical lens antenna.

This paper presents a Q-band transceiver front-end module employing a superheterodyne structure, which includes transmitting circuits and receiving circuits. As for the proposed transceiver fronted-end module, intermediate frequency is fixed at 5.8GHz, the local oscillator(LO) frequency is 34.7-37.7GHz and the LO and IF signal are mixed to obtain a radio frequency(RF) signal operating at 40.5-43.5GHz. In order to suppress the spurious signals, the high-performance LO filter and RF filter are proposed in this paper. The LO filter works at a frequency ranging from 34.5GHz to 39GHz, the measured insertion loss(IL) is less than 3.2dB and return loss(RL) is better than 14dB. Besides, the RF filter works over the operating band of 40.5-43.5GHz, the measured IL is less than 4.3dB and RL is better than 13.8dB. As for the receiving circuits, a −30dB coupler is presented to weaken the strength of the RF signal, the coupling flatness is better than 1dB in the frequency range of 40.5-43.5GHz. In addition, the link budget of the overall circuits are given as follows.

Firstly, this paper discusses several challenges faced by the existing single-vehicle intelligent driving and intense demand for connecting, then proposes the system architecture of the Internet of Vehicles from the perspective of communication capability and application support. Finally, the paper puts forward development strategies for the autonomous driving, forming a global wide recognition.

The specificity hydrogen bonds of nucleobase pairs are the main linker in DNA and RNA. Compared with conventional covalent-linking polymer to prepare nanoparticles (NPs), nucleobase pairs as supermolecule linker to assemble the bionic copolymer NPs may be an innovative way. Adenine (A) modified poly(e-caprolactone) and thymine (T) modified poly(ethylene glycol) are prepared to assemble multiple hydrogen bonds linked NPs in situ. The introduction of multiple hydrogen bonds into NPs results in a unique method to prepare NPs replacing the conventional assemble method. These NPs exhibit narrow size distribution with the average diameter of 45 nm under pH 7.4. The chemical shift of T NH proton moves from 11.30 to 11.05 ppm with increasing temperature from 25 to 80 °C, and the same phenomenon also appears in A NH2 proton resonance, which demonstrate the existence of hydrogen bonds. The low cytotoxicity of NPs is confirmed by MTT assay using MCF7 tumor cells. Collectively, the novel method opens the possibilities to combine bionics in assembling small size nanoparticles.

In this paper, we proposed a new semi-supervised multi-manifold learning method, called semi- supervised sparse multi-manifold embedding (S3MME), for dimensionality reduction of hyperspectral image data. S3MME exploits both the labeled and unlabeled data to adaptively find neighbors of each sample from the same manifold by using an optimization program based on sparse representation, and naturally gives relative importance to the labeled ones through a graph-based methodology. Then it tries to extract discriminative features on each manifold such that the data points in the same manifold become closer. The effectiveness of the proposed multi-manifold learning algorithm is demonstrated and compared through experiments on a real hyperspectral images.

Human tumor cell lines are extremely important tools for cancer research, but a significant percentage is cross-contaminated with other cells. Short tandem repeat (STR) profiling is the prevailing standard for authenticating cell lines that originate from human tissues. Based on the analysis of 482 different human tumor cell lines used in China by STR, up to 96 cell lines were misidentified. More importantly, the study has found that STR profiling alone is insufficient to exclude inter-species cross-contamination of human cell lines. Among the 386 cell lines which had a correct STR profile, 3 of them were inter-species cross-contaminated. Careful microscopic examination may be helpful in some cases to detect changes in morphology but additional testing is needed. Additionally, species verification by PCR could easily identify the contaminants, even with a low percentage of contaminating cells. Combining STR profiling with species identification by PCR, more than 20.5% (99/482) of tumor cell lines were revealed as having been incorrectly identified, including intra-species (14.5%), inter-species (4.4%) cross-contamination and contaminating cell lines (1.7%). Therefore, quality control of cell lines is a systemic issue. Each cell line should undergo a full QA (Quality Assurance) assessment before it is used for research.

Background: Aldehyde dehydrogenase (ALDH) has been widely used as a marker of cancer stem cells (CSCs). However, the ALDH family includes 19 members, and the most relevant isoforms and their biological functions in cancer biology are still controversial. Methods: We examined ALDH enzyme activity and the mRNA expression of 19 ALDH members in 58 human cell lines. The biological effect and mechanism of knocking down ALDH1A3 with siRNA and shRNA in cell lines were explored. Finally, the relationship between ALDH1A3 and CXCR4 was analysed in a large panel of cell lines. Results: ALDH1A3 is the key isoform that contributed to Aldefluor positivity in cell lines. Knocking down ALDH1A3 in different cancer cells conferred opposite phenotypes due to differential effects on CXCR4 expression. There was a significant negative correlation between ALDH1A3 and CXCR4 in 58 human cell lines. Conclusions: ALDH1A3 was the main contributor to Aldefluor positivity in human cell lines, and its contrasting effects might arise from differences in CXCR4 expression.

The morphology of the resultant poly(ethyleneglycol dimethacrylate- co - methacrylic acid)/polydivinylbenzene (P(EGDMA- co -MAA)/PDVB) nanocapsules for in situ precipitation polymerization of divinylbenzene in presence of P(EGDMA- co -MAA) nanocapsules as templates was controlled by the density of the residual surface vinyl group of the P(EGDMA- co -MAA) nanocapsules, which was dependent on the cross-linking degree (EGDMA) for the distillation precipitation copolymerization of EGDMA and MAA. The morphology of P(EGDMA- co -MAA)/PDVB hybrid nanocapsules can be regulated from the separated domains, raspberry-like to a double-layer structure by adjusting the EGDMA cross-linking degree from 20% to 100% for P(EGDMA- co -MAA) nanocapsule templates with various densities of the surface vinyl group. As a result, the well defined raspberry-like P(EGDMA- co -MAA)/PDVB nanocapsules were obtained in presence of P(EGDMA- co -MAA) templates with the intermediate density of surface vinyl group during the precipitation polymerization. The morphology and structure of the P(EGDMA- co -MAA)/PDVB nanocapsules were characterized by Fourier transform infrared analyses (FT-IR), Zeta potential, transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM) and elemental analysis by ion chromatography.

Poly(N,N′-methylenebisacrylamide-co-acrylic acid) microsphere-supported polyamidoamine (PAMAM) dendrimers up to third generation (G) were grown onto the surface as well as the gel-layer of P(MBA-co-MAA) microspheres by a divergent method. The P(MBA-co-MAA) supported PAMAM dendrimers were used as heterogeneous stabilizers for the gold nanoparticles by an in situ reduction of HAuCl4 via the efficient coordination interaction between the amino groups of the supported PAMAM dendrimers and the gold atoms. The effects of the generations of the P(MBA-co-MAA) supported PAMAM dendrimer on the loadings and the catalytic activity of the heterogeneous Au nanoparticles were systematically investigated with the reduction of 4-nitrophenol to 4-aminophenol as a model reaction.

In this paper, we propose a novel manifold learning method, called complete local Fisher discriminant analysis (CLFDA), for face recognition. LFDA often suffers from the small sample size problem, which makes the local within-class scatter matrix singular. In practice, principal component analysis is applied as a preprocessing step to solve this problem. However, this strategy may discard dimensions that contain important discriminative information. The aim of CLFDA is to make full use of two kinds of discriminant information, regular and irregular. At first, CLFDA removes the null space of local within-class scatter to extract the regular discriminant features in the range space of local within-class scatter. Then, the irregular discriminant features are extracted in the null space of local between-class scatter. In addition, we impose Laplacian score to rank the regular and irregular features to achieve the best performance more quickly. Experiments on AT&T, YaleB and CMU PIE face databases are performed to demonstrate the effectiveness of the proposed method.

In this paper, we propose an improved manifold learning method, called uncorrelated local Fisher discriminant analysis (ULFDA), for ear recognition. Motivated by the fact that the features extracted by local Fisher discriminant analysis are statistically correlated, which may result in poor performance for recognition. The aim of ULFDA is to seek a feature submanifold such that the within-manifold scatter is minimized and between-manifold scatter is maximized simultaneously in the embedding space by using a new difference-based optimization objective function. Moreover, we impose an appropriate constraint to make the extracted features statistically uncorrelated. As a result, the proposed algorithm not only derives the optimal and lossless discriminative information, but also guarantees that all extracted features are statistically uncorrelated. Experiments on synthetic data and Spain, USTB-2 and CEID ear databases are performed to demonstrate the effectiveness of the proposed method.

An improved manifold learning method, called Uncorrelated Local Fisher Discriminant Analysis (ULFDA), for face recognition is proposed. Motivated by the fact that statistically uncorrelated features are desirable for dimension reduction, we propose a new difference-based optimization objective function to seek a feature submanifold such that the within-manifold scatter is minimized, and between-manifold scatter is maximized simultaneously in the embedding space. We impose an appropriate constraint to make the extracted features statistically uncorrelated. The uncorrelated discriminant method has an analytic global optimal solution, and it can be computed based on eigen decomposition. As a result, the proposed algorithm not only derives the optimal and lossless discriminative information, but also guarantees that all extracted features are statistically uncorrelated. Experiments on synthetic data and AT&T, extended YaleB and CMU PIE face databases are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of the proposed method.

A general method was developed for the synthesis of Fe3O4@polymer microspheres with well-defined core–shell structure and various functional groups and strong magnetization through a facile in situ distillation–precipitation polymerization. In this approach, the as-prepared Fe3O4 microspheres were directly coated by a polymer shell through the hydrogen bond interaction between the Fe3O4 micropsheres and oligomer without any surface modification. Moreover, hydrophilic or hydrophobic monomer or even their comonomers with different functional groups such as carboxyl, hydroxyl, amide, and ester were facilely encapsulated onto the surface of the magnetite microspheres. The thickness of the polymer shell layer was tuned by the feed of monomer amount. As for application, Fe3O4@P(MBAAm-co-MAA) microspheres that contained carboxyl groups were used as a magnetic catalyst support to load a series of metallic nanoparticles such as Ag, Pt, and Au. These strong magnetic microspheres were characterized by transmission e...

CD133 has been identified as a cancer stem cell marker in colon and several other cancers, but its function is still unknown. We examined the CD133 expression in 44 human cancer cell lines, and found five of the 8 positive lines were from colon cancer. The CD133 positive subpopulation of colon cancer cells showed more vigorous growth and lower differentiation. Induction of differentiation reduced the CD133-positive population. Knockdown of CD133 expression in colon cancer cells could not induce cellular differentiation. Care must be taken if CD133 is used as the only marker of cancer stem cells in colon cancer, especially in established cell lines. CD133 negatively correlates with cell differentiation, but it is not a regulator of differentiation.

Automatic face recognition is a challenging problem in the biometrics area, where the dimension of the sample space is typically larger than the number of samples in the training set and consequently the so-called small sample size problem exists. Recently, neuroscientists emphasized the manifold ways of perception, and showed the face images may reside on a nonlinear submanifold hidden in the image space. Many manifold learning methods, such as Isometric feature mapping, Locally Linear Embedding, and Locally Linear Coordination are proposed. These methods achieved the submanifold by collectively analyzing the overlapped local neighborhoods and all claimed to be superior to such subspace methods as Eigenfaces and Fisherfaces in terms of classification accuracy. However, in literature, no systematic comparative study for face recognition is performed among them. In this paper, we carry out a comparative study in face recognition among them, and the study considers theoretical aspects as well as simulations performed using CMU PIE and FERET face databases.

The performance of automatic fingerprint identification system relies heavily on the quality of fingerprint images. Fingerprint enhancement is essential to ensure the robustness of fingerprint identification with respect to the image quality. Gabor filtering is the most popular method in fingerprint enhancement. To overcome the limitations of traditional Gabor filter and promote fingerprint enhancement performance, the Log-Gabor filter is introduced in this paper. The design method and implementation scheme of Log-Gabor filter in fingerprint enhancement are described in detail. The enhancement performance is assessed on standard fingerprint databases. Experimental results show that the proposed Log-Gabor filtering method can effectively improve the fingerprint image quality and promote the reliability of fingerprint identification.

To establish a murine uterine cervical cancer cell line and to define its biological characters. Transplanted tumor tissue was used for in vitro primary culture of U14 cervical carcinoma cells. After 20 passages, we examined its morphology, chromosomes, tumorigenicity and produced a growth curve. CK was detected by immunohistochemistry, the cell cycle determined by flow cytometry and the metastatic potential assessed in 615 and C57BL/c mice. We also transfected the cells with the pEGFP-N1 plasmid. A newly established murine cell line was passaged 50 times over a period of 10 months. The cells grow as a partially suspended culture, and are immunohistochemically CK(+). The cell line is characterized by a hypotetraploid karyotype, a chromosomal number of 64–68 and a doubling time of 21.8 h. Exponential growth occurs by the third and forth day of culture. Cell cycle analysis showed G1 34%, G2 26%, and 40% in the S phase. The tumorigenicity was 100% upon implantation. No mycoplasma contamination was detected. A monoclonal continuous U14-GFP cell strain which was 100% GFP (+) was also produced. We successfully established a new murine cervical U14 carcinoma cell line and an U14-GFP monoclonal strain. These cell lines are ideal for combined in vivo and in vitro tumor research.

Backgrounds: Epidermal growth factor (EGF) is a 53 amino acid polypeptide and its receptor EGFR is an established therapeutic target for anti-tumor therapy. Two major categories of EGFR-targeted drugs include monoclonal antibodies (mAbs) and small molecular tyrosine kinase inhibitors (TKIs). However, drug resistance occurs in a significant proportion of patients due to EGFR mutations. Since EGFR can maintain activation while abrogating the activity of mAbs or TKIs, or bypass signaling functions while successfully circumventing the EGF-EGFR switch, developing new mechanism-based inhibitors is necessary. Methods: In this study, based on the principle of tumor immunotherapy, a recombinant protein pLLO-hEGF was constructed. The N-terminal portion contains three immunodominant epitopes from listeriolysin O (LLO) and the C-terminal includes EGF. To use EGF as a target vector to recognize EGFR-expressing cancer cells, immunodominant epitopes could enhance immunogenicity of tumor cells for immune cell activation and attack. Results: Recombinant protein pLLO-hEGF was successfully expressed and showed strong affinity to cancer cells. Also, pLLO-hEGF could significantly stimulate human lymphocyte proliferation and the lymphocytes demonstrated enhanced killing potency in EGFR-expressing cancer cells in vitro and in vivo. Conclusion: This study can provide novel strategies and directions in tumor biotherapy.

To evaluate the effect of combined targeting of MEK and PI3K signaling pathways on K-ras mutated non-small cell lung cancer cell line A549 cells and the relevant mechanisms.A549 cells were treated with different concentrations of two inhibitors. Growth inhibition was determined by MTT assay. According to the results of MTT test, the cells were divided into four groups: the control group, PI3K inhibitor group (GDC-0941,0.5 and 5.0 µmol/L), combination group I (0.5 µmol/L AZD6244+0.5 µmol/L GDC-0941) and combination group II (5.0 µmol/L AZD6244+5.0 µmol/L GDC-0941). The cell cycle and apoptosis were analyzed by flow cytometry. The expression of proteins related to apoptosis was tested with Western blot.Both GDC-0941 and AZD6244 inhibited the cell proliferation. The combination group II led to a stronger growth inhibition. The combination group I showed an antagonistic effect and combination group II showed an additive or synergistic effect. Compared with the control group, the combination group I led to reduced apoptotic rate [(20.70 ± 0.99)% vs. (18.65 ± 0.92 )%, P0.05]; Combination group II exhibited enhanced apoptotic rate [(37.85 ± 3.18)% vs. (52.27 ± 4.36)%, P0.01]. In addition, in the combination group II, more A549 cells were arrested in G0/G1 phase and decreased S phase (P0.01), due to the reduced expressions of CyclinD1 and Cyclin B1, the increased cleaved PARP and the diminished ratio of Bcl-2/Bax.For single K-ras mutated NSCLC cell line A549 cells, combination of RAS/MEK/ERK and PI3K/AKT/mTOR inhibition showed synergistic effects depending on the drug doses. Double pathways targeted therapy may be beneficial for these patients.

Colon cancer is associated with increased cell migration and invasion. In the present study, the role of ubiquitin-specific peptidase 22 (USP22) in signal transducer and activator of transcription 3 (STAT3)-mediated colon cancer cell invasion was investigated. The messenger RNA levels of STAT3 target genes were measured by reverse transcription-quantitative polymerase chain reaction, following USP22 knockdown by RNA interference in SW480 colon cancer cells. The matrix metalloproteinase 9 (MMP9) proteolytic activity and invasion potential of SW480 cells were measured by zymography and Transwell assay, respectively, following combined USP22 and STAT3 short interfering (si)RNA treatment or STAT3 siRNA treatment alone. Similarly, a cell counting kit-8 assay was used to detect the proliferation potential of SW480 cells. The protein expression levels of USP22, STAT3 and MMP9 were detected by immunohistochemistry in colon cancer tissue microarrays (TMAs) and the correlation between USP22, STAT3 and MMP9 was analyzed. USP22/STAT3 co-depletion partly rescued the MMP9 proteolytic activity and invasion of SW480 cells, compared with that of STAT3 depletion alone. However, the proliferation of USP22/STAT3si-SW480 cells was decreased compared with that of STAT3si-SW480 cells. USP22 expression was positively correlated with STAT3 and MMP9 expression in colon cancer TMAs. In conclusion, USP22 attenuated the invasion capacity of colon cancer cells by inhibiting the STAT3/MMP9 signaling pathway.

CD133 is widely expressed in colorectal cancer (CRC) tissues and cell lines. This protein has been used as a marker of CRC cancer stem cells, although the function and mechanism of CD133 in CRC invasion and metastasis remain unclear. In our study, we examined the role of CD133 in CRC invasion in vitro and investigated the mechanism involved in CD133-related invasion. CD133 high and CD133 low HCT116 cells were isolated, and the proliferation and invasive ability of these two subpopulations were tested. CD133 high HCT116 cells exhibited greater proliferation and invasion compared with CD133 low HCT116 cells. CD133 knockdown (using CD133 small-interfering [si]RNA) inhibited the invasive activity of CD133si-HCT116 cells. For the first time, we found that the expression of tissue inhibitor of matrix metalloproteinases-2 (TIMP-2) was down-regulated in CD133si-HCT116 cells. In addition, for the TIMP-2si-HCT116 cells (transfected with TIMP-2 siRNA), in vitro invasion was significantly decreased, whereas the expression of CD133 remained unchanged. Finally, the metalloproteinase 2 and MEK/ERK signaling pathways were examined, and no significant change was observed after the knockdown of CD133 or TIMP-2 in HCT116 cells. In conclusion, we demonstrated that CD133 plays an important role in HCT116 cell invasion, and for the first time, we found that CD133 knockdown significantly down-regulated TIMP-2 expression, which suggests that CD133 affects the invasive ability of HCT116 cells by regulating TIMP-2.

SiO(2)/poly(ethyleneglycol dimethacrylate) (PEGDMA) rattle-type microspheres loaded with tiny sized gold nanoparticles (~2 nm) were prepared through a facile and novel method. Catalyzed reduction of 4-nitrophenol with NaBH(4) demonstrated that this rattle-type microsphere possessed high catalytic efficiency.

SRS19-6MuLV is a member of the MuLV family originally isolated from the Tianjin-Shanghai-Zunyi complex of murine leukemia. A notable characteristic of this virus is that it induces tumors of multiple hematopoietic lineages, including myeloid, erythroid, T-lymphoid and B-lymphoid. In a previous study, a sequence with high homology to SRS19-6MuLV in a murine dendritic cell sarcoma (DCS) was identified through cDNA expression screening with mAb 983D4. To investigate the relationship between SRS19-6MuLV and DCS, the existence of a specific SRS19-6MuLV DNA fragment in DCS cells, 15 murine tumor cells, 2 murine tumor tissues, 12 normal murine cells/tissues, 11 human tumor cell lines and SRSV/3T3 (NIH/3T3 cells infected with SRS cell supernatant) was detected by PCR. The specific fragment of SRS19-6MuLV was detected in DCS, mouse fore-gastric cancer cells, LⅡ tumor tissue from which DCS is derived and SRSV/3T3. In addition, the integration sites of SRS19-6MuLV in the positive cells were examined by inverse PCR. Thus, 7 integration sites for SRS19-6MuLV were detected in DCS and 3 in SRSV/3T3. Analysis of sequences by BLAST revealed that some of the integration sites were associated with common fragile sites and some Ras-regulating miRNAs. Our results indicate that SRS19-6MuLV not only induced four types of leukemia, but also induced DCS. This virus does not infect human cells. Multiple integration of SRS19-6MuLV into chromosomes around fragile sites accounts for its carcinogenic effects.

This paper presents a physical layer transmission solution of satellite interactive communication system, which takes LDPC code as part of FEC scheme and handles control data and payload in the same way. With this method, hardware design is simplified and error floor is decreased.

This paper introduces the generation principle of DTMF(Double Tone Multi Frequency) signaling at first, and describes the method that how DTMF signaling is inserted into the time slot of the audio signal which would be carried by AM medium-wave. An implementation scheme of AM medium-wave emergency broadcasting based on DTMF signaling insertion technology is proposed in this paper, meanwhile, the emergency broadcasting message receiving method and system structure based on DTMF signaling control are described in detail. It is provided that a feasible technology implementation scheme for popularization and application of medium-wave emergency broadcasting.

An improved manifold learning method, called enhanced semi-supervised local fisher discriminant analysis (ESELF), for gene expression data classification is proposed. Motivated by the fact that semi-supervised and parameter-free are two desirable and promising characteristics for dimension reduction, a new difference-based optimization objective function with unlabeled samples has been designed. The proposed method preserves the global structure of unlabeled samples in addition to separating labeled samples in different classes from each other. The semi-supervised method has an analytic form of the globally optimal solution and it can be computed based on eigen decompositions. The experimental results and comparisons on synthetic data and two DNA micro array datasets demonstrate the effectiveness of the proposed method.

The effect of image quality on the performance of multimodal biometric verification is studied. A biometric system based solely on single modality is often not able to meet the system performance requirements for poor image quality. Prior studies of multimodal biometric authentication have shown that it can improve performance over use of a single unimodal biometric. The well-known multimodal methods do not consider the quality information of the data used when combining the results from different matchers. In the paper, a novel SVM-based multimodal biometric authentication system is presented. It is based on SVM classifiers and quality measures of the input biometric signals. Experimental results on a prototype application based on fingerprint and face are reported. The proposed scheme is shown to outperform significantly multimodal systems without considering quality signals and unimodal systems over a wide range of image quality.

Feature selection has attracted a huge amount of interest in both research and application communities of hyperspectral image (HSI) classification. Generally, supervised feature selection methods are superior to unsupervised ones without label information. However, in classification of HSI, the labeled samples are often difficult, expensive or time-consuming to obtain. In this paper, we proposed a novel semi-supervised feature selection method, called Locality and Globality Discriminant Feature (LGDF), for HSI classification. This method combines Fisher's criteria and Graph Laplacian, which makes full use of both labeled and unlabeled data points to discover both manifold and discriminant structure in HSI data. In the proposed method, an optimal subset of features is identified if at this subset neighbor points or points sharing the same label are close to each other, while non-neighbor points or points with different labels are far away from each other. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral datasets demonstrate the effectiveness of the proposed method.

Many efforts have been devoted to maintaining the water content at a constant level in water retention proton exchange membranes, especially under a low humidity. It is necessary to develop a method for enhancing the water retention with a stable dynamic water behavior. Herein, humidity responsive double-shelled hollow spheres (DSHSs) were incorporated into a sulfonated poly(ether ether ketone) (SPEEK) matrix membrane to simultaneously enhance its water retention and improve its dynamic water behavior. The water retention of the DSHS incorporated SPEEK membrane was considerably increased compared to that of the SPEEK membrane due to the presence of a central cavity and gap between the inner and outer shell of the DSHSs. The humidity responsive DSHSs could rapidly adjust the water distribution within the SPEEK matrix and compensate the water evaporated under a low humidity, which is similar to the function of a vacuole in plant cells. As a result, the dynamic water behavior of the SPEEK/DSHS hybrid membranes was significantly improved. As a benefit from this, a continuous water network in the hybrid membranes could be maintained for a long time to enhance the proton conductivity of the hybrid membranes under a low humidity. A mechanism was proposed for the interpretation of these phenomena. The nanostructure of the hybrid membranes was studied by small-angle X-ray scattering (SAXS) and field emission scanning electron microscopy (FESEM).