A Novel Underwater Acoustic Target Recognition Method Based on MFCC and RACNN.

In ocean remote sensing missions, recognizing an underwater acoustic target is a crucial technology for conducting marine biological surveys, ocean explorations, and other scientific activities that take place in water. The complex acoustic propagation characteristics present significant challenges for the recognition of underwater acoustic targets (UATR). Methods such as extracting the DEMON spectrum of a signal and inputting it into an artificial neural network for recognition, and fusing the multidimensional features of a signal for recognition, have been proposed. However, there is still room for improvement in terms of noise immunity, improved computational performance, and reduced reliance on specialized knowledge. In this article, we propose the Residual Attentional Convolutional Neural Network (RACNN), a convolutional neural network that quickly and accurately recognize the type of ship-radiated noise. This network is capable of extracting internal features of Mel Frequency Cepstral Coefficients (MFCC) of the underwater ship-radiated noise. Experimental results demonstrate that the proposed model achieves an overall accuracy of 99.34% on the ShipsEar dataset, surpassing conventional recognition methods and other deep learning models.

Multifunctional transmission-type microwave metadevice based on spin-decoupled and linear-to-circular metasurfaces.

Metasurfaces have enabled precise electromagnetic (EM) wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices. One promising aspect to achieve multifunction is polarization-dependent metadevices enabled by simultaneous phase control over orthogonally polarized waves. Among these, metasurfaces with geometric phase shows their natural and robust phase control ability over different circularly polarized waves. However, the phase responses under the circularly polarized incidence are locked to be opposite with each other, resulting in limited multifunctionality. In this study, we propose what we believe to be a novel transmission-type microwave metadevice constructed by linear-to-circular metasurface and spin-decoupled metasurface. By endowing independent phase adjustment capability to each unit structure in a spin-decoupled metasurface, the metadevice can reconfigure arbitrary phase wavefronts under orthogonal polarization state incidence, thereby achieving flexible multifunctionality. As a proof-of-concept, the feasibility and reliability of proposed metasurfaces were verified by simulating multifunctional directional deflection, off-axis focusing, and focused vortex beam generation. Finally, the multifunctional manipulation capability of the metadevice is successfully demonstrated by actually measuring the generation of orbital angular momentum modes. This work is expected to drive the application development of metasurface devices in wireless communication.

Multi-View Clustering With Graph Learning for scRNA-Seq Data.

Advances in single-cell biotechnologies have generated the single-cell RNA sequencing (scRNA-seq) of gene expression profiles at cell levels, providing an opportunity to study cellular distribution. Although significant efforts developed in their analysis, many problems remain in studying cell types distribution because of the heterogeneity, high dimensionality, and noise of scRNA-seq. In this study, a multi-view clustering with graph learning algorithm (MCGL) for scRNA-seq data is proposed, which consists of multi-view learning, graph learning, and cell type clustering. In order to avoid a single feature space of scRNA-seq being inadequate to comprehensively characterize the functions of cells, MCGL constructs the multiple feature spaces and utilizes multi-view learning to comprehensively characterize scRNA-seq data from different perspectives. MCGL adaptively learns the similarity graphs of cells that overcome the dependence on fixed similarity, transforming scRNA-seq analysis into the analysis of multi-view clustering. MCGL decomposes the networks of cells into view-specific and common networks in multi-view learning, which better characterizes the topological relationship of cells. MCGL simultaneously utilizes multiple types of cell-cell networks and fully exploits the connection relationship between cells through the complementarity between networks to improve clustering performance. The graph learning, graph factorization, and cell-type clustering processes are accomplished simultaneously under one optimization framework. The performance of the MCGL algorithm is validated with ten scRNA-seq datasets from different scales, and experimental results imply that the proposed algorithm significantly outperforms fourteen state-of-the-art scRNA-seq algorithms.

Multi-View Clustering for Integration of Gene Expression and Methylation Data With Tensor Decomposition and Self-Representation Learning.

The accumulated DNA methylation and gene expression provide a great opportunity to exploit the epigenetic patterns of genes, which is the foundation for revealing the underlying mechanisms of biological systems. Current integrative algorithms are criticized for undesirable performance because they fail to address the heterogeneity of expression and methylation data, and the intrinsic relations among them. To solve this issue, a novel multi-view clustering with self-representation learning and low-rank tensor constraint (MCSL-LTC) is proposed for the integration of gene expression and DNA methylation data, which are treated as complementary views. Specifically, MCSL-LTC first learns the low-dimensional features for each view with the linear projection, and then these features are fused in a unified tensor space with low-rank constraints. In this case, the complementary information of various views is precisely captured, where the heterogeneity of omic data is avoided, thereby enhancing the consistency of different views. Finally, MCSL-LTC obtains a consensus cluster of genes reflecting the structure and features of various views. Experimental results demonstrate that the proposed approach outperforms state-of-the-art baselines in terms of accuracy on both the social and cancer data, which provides an effective and efficient method for the integration of heterogeneous genomic data.

Tunable Terahertz Wavefront Modulation Based on Phase Change Materials Embedded in Metasurface.

In the past decades, metasurfaces have shown their extraordinary abilities on manipulating the wavefront of electromagnetic wave. Based on the ability, various kinds of metasurfaces are designed to realize new functional metadevices based on wavefront manipulations, such as anomalous beam steering, focus metalens, vortex beams generator, and holographic imaging. However, most of the previously proposed designs based on metasurfaces are fixed once design, which is limited for applications where light modulation needs to be tunable. In this paper, we proposed a design for THz tunable wavefront manipulation achieved by the combination of plasmonic metasurface and phase change materials (PCMs) in THz region. Here, we designed a metal-insulator-metal (MIM) metasurface with the typical C-shape split ring resonator (CSRR), whose polarization conversion efficiency is nearly 90% for circular polarized light (CPL) in the range of 0.95~1.15 THz when PCM is in the amorphous state, but the conversion efficiency turns to less than 10% in the same frequency range when PCM switches into the crystalline state. Then, benefiting from the high polarization conversion contrast of unit cell, we can achieve tunable wavefront manipulation by utilizing the Pancharatnam-Berry (PB) phase between the amorphous and crystalline states. As a proof-of-concept, the reflective tunable anomalous beam deflector and focusing metalens are designed and characterized, and the results further verify their capability for tunable wavefront manipulation in THz range. It is believed that the design in our work may pave the way toward the tunable wavefront manipulation of THz waves and is potential for dynamic tunable THz devices.

Automatic and inverse design of broadband terahertz absorber based on optimization of genetic algorithm for dual metasurfaces.

In this study, we introduce a genetic algorithm (GA) into the catenary theory model to achieve automatic and inverse design for terahertz (THz) metasurface absorbers. The GA method was employed by seeking optimal dispersion distributions to achieve broadband impedance matching. A THz dual-metasurface absorber was designed using the proposed approach. The designed metasurface absorber exhibits an absorbance exceeding 88% at 0.21-5 THz. Compared to the traditional design method, the proposed method can reduce time consumption and find the optimal result to achieve high performance. The investigations provide important guidance and a promising approach for designing metasurface-based devices for practical applications.

Multi-Angle Optical Image Automatic Registration by Combining Point and Line Features.

Image registration is an important basis of image processing, which is of great significance in image mosaicking, target recognition, and change detection. Aiming at the automatic registration problem of multi-angle optical images for ground scenes, a registration method combining point features and line features to register images is proposed. Firstly, the LSD (Line Segment Detector) algorithm is used to extract line features of images. The obtained line segments whose length are less than a given threshold are eliminated by a visual significant algorithm. Then, an affine transform model obtained by estimating a Gaussian mixture model (GMM) is applied to the image to be matched. Lastly, Harris point features are utilized in fine matching to overcome shortages of methods based on line features. In experiments, the proposed algorithm is compared with popular feature-based registration algorithms. The results indicate that the proposed algorithm in this work has obvious advantages in terms of registration accuracy and reliability for optical images acquired at different angles.

Prospective memory performance in non-psychotic first-degree relatives of patients with schizophrenia: a controlled study.

OBJECTIVE: We aimed at investigating prospective memory and its socio-demographic and neurocognitive correlates in non-psychotic, first-degree relatives (FDRs) of patients with schizophrenia compared to patients with first episode schizophrenia (FES), and healthy controls (HCs). METHODS: Forty-seven FES patients, 50 non-psychotic FDRs (23 offspring and 27 siblings) of patients with chronic schizophrenia (unrelated to the FES group) and 51 HCs were studied. The Chinese version of the Cambridge Prospective Memory Test (C-CAMPROMPT) was used to measure time-based prospective memory (TBPM) and event-based prospective memory (EBPM) performance. Other cognitive functions (involving respective memory and executive functions) were evaluated with standardized tests. RESULTS: After controlling for basic demographic characteristics including age, gender and educational level, there was a significant difference between FDRs, FES and HCs with respect to both TBPM (F(2,142) = 10.4, p<0.001) and EBPM (F(2,142) = 10.8, p<0.001). Multiple linear regression analyses revealed that lower scores of the Hopkins Verbal Learning Test-Revised (HVLT-R) and the STROOP Word-Color Test (SWCT) contributed to TBPM impairment, while lower educational level and higher scores of the Color Trails Test-2 (CTT-2) contributed to EBPM deficit in FDRs. CONCLUSIONS: FDRs share similar but attenuated prospective memory impairments with schizophrenia patients, suggesting that prospective memory deficits may represent an endophenotype of schizophrenia.

Effect of nonionic compound emulsifiers Tween80 and Span80 on the properties of microencapsulated phase change materials.

In this article, the nonionic compound emulsifiers Tween80 and Span80 were used to prepare microcapsules containing phase change materials (microPCMs) with melamine-formaldehyde (MF) shells by in situ polymerization method. The effects of compound emulsifiers Tween80 and Span80 on the structure, morphologies and properties of microPCMs containing paraffin were studied. SEM morphological investigation suggests that a complex of Tween80 and Span80 as emulsifiers are optimal for the fabrication of microPCMs in this study compared to Tween60 or OP-10. The diameter distributions of microPCMs synthesized with different amounts of compound emulsifiers are uniform, whereas compound emulsifiers' amount affect the mean diameter of microPCMs decreasing from 5.34 to 3.05 µm. These microPCMs with the core/shell weight ratio 3/1 have smoother surface and a higher core content of 68.7% than other core/shell ratio. Anti-osmosis measurements indicate that microPCMs have good compactness and stable performance compared to those synthesized by one type of emulsifier.

Improved recovery and identification of membrane proteins from rat hepatic cells using a centrifugal proteomic reactor.

Despite their importance in many biological processes, membrane proteins are underrepresented in proteomic analysis because of their poor solubility (hydrophobicity) and often low abundance. We describe a novel approach for the identification of plasma membrane proteins and intracellular microsomal proteins that combines membrane fractionation, a centrifugal proteomic reactor for streamlined protein extraction, protein digestion and fractionation by centrifugation, and high performance liquid chromatography-electrospray ionization-tandem MS. The performance of this approach was illustrated for the study of the proteome of ER and Golgi microsomal membranes in rat hepatic cells. The centrifugal proteomic reactor identified 945 plasma membrane proteins and 955 microsomal membrane proteins, of which 63 and 47% were predicted as bona fide membrane proteins, respectively. Among these proteins, >800 proteins were undetectable by the conventional in-gel digestion approach. The majority of the membrane proteins only identified by the centrifugal proteomic reactor were proteins with ≥ 2 transmembrane segments or proteins with high molecular mass (e.g. >150 kDa) and hydrophobicity. The improved proteomic reactor allowed the detection of a group of endocytic and/or signaling receptor proteins on the plasma membrane, as well as apolipoproteins and glycerolipid synthesis enzymes that play a role in the assembly and secretion of apolipoprotein B100-containing very low density lipoproteins. Thus, the centrifugal proteomic reactor offers a new analytical tool for structure and function studies of membrane proteins involved in lipid and lipoprotein metabolism.

Lyso-form fragment ions facilitate the determination of stereospecificity of diacyl glycerophospholipids.

In this work we report the development of a novel methodology for the determination of stereospecificity of diacyl glycerophospholipids, including glycerophosphatidic acids (PA), glycerophosphoserines (PS), glycerophosphoglycerols (PG), glycerophosphoinositols (PI), and glycerophosphoethanolamines (PE), which can be conventionally ionized in negative ion mode. This methodology uses MS(2) recorded on a hybrid quadrupole time-of-flight mass spectrometer to determine the stereospecificity of diacyl glycerophospholipids based on the lyso-form fragment ions, attributed to the neutral loss of fatty acyl moieties. The fragmentation patterns of a variety of diacyl glycerophospholipid standards were first fully examined over a wide range of collision energy. We observed that lyso-form fragment ions corresponding to the neutral loss of fatty acyl moieties attached to the sn2 position as free fatty acids ([M-Sn2](-) ) and as ketenes ([M-(Sn2-H(2) O)](-) ) exhibited consistently higher intensity than their counterpart ions due to the neutral loss of fatty acyl moieties attached to the sn1 position ([M-Sn1](-) and [M-(Sn1-H(2) O)](-) ). Therefore, we concluded that an empirical fragmentation rule can be used to precisely determine the stereospecificity of diacyl glycerophospholipids, primarily on the basis of relative abundance of the lyso-form fragment ions. We then examined the product ion spectra of diacyl glycerophospholipids recorded from lipid extracts of rat hepatoma cells, where the stereospecific information of these lipids was conclusively determined. Combining the novel methodology reported in this work with the currently widely practiced mass spectrometric techniques such as multiple precursor ion scans (MPIS), fatty acyl scans (FAS), and multidimensional mass spectrometry based shotgun lipidomics (MDMS-SL), should enable a reliable and convenient platform for comprehensive glycerophospholipid profiling.

Lipidomics era: accomplishments and challenges.

Lipid mediators participate in signal transduction pathways, proliferation, apoptosis, and membrane trafficking in the cell. Lipids are highly complex and diverse owing to the various combinations of polar headgroups, fatty acyl chains, and backbone structures. This structural diversity continues to pose a challenge for lipid analysis. Here we review the current state of the art in lipidomics research and discuss the challenges facing this field. The latest technological developments in mass spectrometry, the role of bioinformatics, and the applications of lipidomics in lipid metabolism and cellular physiology and pathology are also discussed.

Controlled deposition of highly oriented type I collagen mimicking in vivo collagen structures.

The structural arrangement of type I collagen in vivo is critical for the normal functioning of tissues, such as bone, cornea, and blood vessels. At present, there are no low-cost techniques for fabricating aligned collagen structures for applications in regenerative medicine. Here, we report a straightforward approach to fabricate collagen films, with defined orientation of collagen fibrillar aggregates within a matrix of oriented collagen molecules. Langmuir-Blodgett (LB) technology was used to deposit thin films of oriented type I collagen onto substrates. It was found that collagen does not behave like classical LB materials, such as amphiphilic hydrocarbon acids or lipids. The thickness of the deposited collagen films and the area-pressure isotherms were found to depend on the amount of material spread. In addition, no film collapse was detected and the deposited LB films were thicker than the theoretical dimension of a collagen monolayer (1.5 nm) formed by triple helical collagen molecules. Individual LB films with thicknesses of up to 20 nm were obtained, and multiple depositions yielded overall film thicknesses of up to 100 nm. Films consisted of a matrix of collagen molecules containing thicker fibrillar aggregates of collagen (micrometers in length). These fibrillar aggregates were built up of shorter unit molecules forming "spun thread" structures, some of which exhibited a zigzag pattern. In addition to aligning collagen unidirectionally (similar for example to tendon), we performed a two-step deposition procedure, in which the substrate was turned 90 degrees between two consecutive collagen deposition steps. The resulting films showed orthogonally aligned collagen layers, mimicking the structure of cornea. Thus, this technique permits control of the thickness of individual layers, the orientation of successive layers, and the number of layers within the construct. Therefore, it may have widespread applicability for the engineering of collagen-rich tissues.

New ammunition for the proteomic reactor: strong anion exchange beads and multiple enzymes enhance protein identification and sequence coverage.

The enrichment and processing of proteomic samples prior to multi-dimensional chromatography remain a challenge in 'gel-free' proteomics. We previously reported the development of a microfluidic device called the "proteomic reactor" that relied on enriching proteins by using strong cation exchange (SCX) followed by trypsin digestion in an interstitial volume as little as 50 nL. Here, we report a novel proteomic reactor that is based on polymeric strong anion exchange (SAX) material to analyse proteomic samples. We also compare the performance of the SAX proteomic reactor to our previously reported SCX proteomic reactor for analysing complex yeast proteomes. Our results indicate that the SAX protein reactor preferentially identifies more acidic peptides and proteins compared to the SCX reactor. We show that the SAX and SCX reactors are complementary and that their combination increases the number of unique peptides and proteins identified by 50%. Furthermore, we show that the number of protein identified can be increased further by up to 40% using different proteolytic enzymes on the proteomic reactor.

Analysis of the subcellular phosphoproteome using a novel phosphoproteomic reactor.

Protein phosphorylation is an important post-translational modification involved in the regulation of many cellular processes. Mass spectrometry has been successfully used to identify protein phosphorylation in specific pathways and for global phosphoproteomic analysis. However, phosphoproteomics approaches do not evaluate the subcellular localization of the phosphorylated forms of proteins, which is an important factor for understanding the roles of protein phosphorylation on a global scale. The in-depth mapping of protein phosphorylation at the subcellular level necessitates the development of new methods capable of specifically and efficiently enriching phosphopeptides from highly complex samples. Here, we report a novel microfluidic device called the phosphoproteomic reactor that combines efficient processing of proteins followed by phosphopeptide enrichment by Ti-IMAC. To illustrate the potential of this novel technology, we mapped the phosphoproteins in subcellular organelles of liver cells. Fifteen subcellular fractions from liver cell cultures were processed on the phosphoproteomic reactor in combination with nano-LC-MS/MS analysis. We identified thousands of phosphorylation sites in over 600 phosphoproteins in different organelles using minute amounts of starting material. Overall, this approach provides a new avenue for studying the phosphoproteome of the subcellular organelles.

Analysis of low-abundance proteins using the proteomic reactor with pH fractionation.

We developed a new method consisting of the proteomic reactor coupled with step pH fractionation for the analysis of low-abundance proteins from minute amount of sample. These new reactors were implemented using both SAX and SCX materials. The pH fractions from the SAX reactor provided higher peptide and protein identification than SCX reactor and conventional solution digestion. Interestingly, the physical characteristics (pI, molecular weight, missed cleavage site and grand average hydrophobicity (GRAVY) index, and number of acid and basic amino acid) of the peptides obtained from the SAX and SCX proteomic reactors are drastically different. Furthermore, nearly half of the peptides observed from the pH fractionations from the SAX reactor are of low abundance while only 22% low-abundance proteins are observed with conventional in-solution digestion following 2D LC-MS/MS analysis.

Amyloid-beta42 signals tau hyperphosphorylation and compromises neuronal viability by disrupting alkylacylglycerophosphocholine metabolism.

Perturbation of lipid second messenger networks is associated with the impairment of synaptic function in Alzheimer disease. Underlying molecular mechanisms are unclear. Here, we used an unbiased lipidomic approach to profile alkylacylglycerophosphocholine second messengers in diseased tissue. We found that specific isoforms defined by a palmitic acid (16:0) at the sn-1 position, namely 1-O-hexadecyl-2-acetyl-sn-glycero-3-phosphocholine (C16:0 PAF) and 1-O-hexadecyl-sn-glycero-3-phosphocholine (C16:0 lyso-PAF), were elevated in the temporal cortex of Alzheimer disease patients, transgenic mice expressing human familial disease-mutant amyloid precursor protein, and human neurons directly exposed to amyloid-beta(42) oligomers. Acute intraneuronal accumulation of C16:0 PAF but not C16:0 lyso-PAF initiated cyclin-dependent kinase 5-mediated hyperphosphorylation of tau on Alzheimer disease-specific epitopes. Chronic elevation caused a caspase 2 and 3/7-dependent cascade resulting in neuronal death. Pharmacological inhibition of C16:0 PAF signaling, or molecular strategies increasing hydrolysis of C16:0 PAF to C16:0 lyso-PAF, protected human neurons from amyloid-beta(42) toxicity. Together, these data provide mechanistic insight into how disruptions in lipid metabolism can determine neuronal response to accumulating oligomeric amyloid-beta(42).

Glycoproteomic reactor for human plasma.

We describe the development of a glycoproteomic reactor that combines multiple biochemical and chemical protein processing into a single device for the study of N-glycosylated proteins. The glycoproteins are first enriched by concanavalin A affinity chromatography and then transferred onto and efficiently processed in the glycoproteomic reactor. This glycoproteomic reactor combines protein concentration and purification, disulfide bond reduction, peptide-N-glycosidase-mediated (18)O-labeling and deglycosylation, alkylation, tryptic digestion and pH based fractionation in a device that has an interstitial volume (reaction volume) of approximately 1 microL. We demonstrated the potential of the glycoproteomic reactor using human plasma. Under stringent criteria, 82 unique glycopeptides representing 41 unique glycoproteins were identified from as little as 5 microL of human plasma. Our glycoproteomic reactor reduces the sample processing time to less than 1.5 h, reduces the reagent consumption while providing over 1000-fold concentration of the sample, provides efficient removal of high concentration of glycan buffer, and, finally, allows both glycopeptides and nonglycosylated tryptic peptides to be analyzed by the mass spectrometer which provides much greater protein coverage and more reliable identifications.

Identification of lysophosphatidylcholine (LPC) and platelet activating factor (PAF) from PC12 cells and mouse cortex using liquid chromatography/multi-stage mass spectrometry (LC/MS3).

Lipids play essential roles in cellular structural support, energy storage and signal transduction. Recently, mass spectrometry (MS) has been used to produce three-dimensional maps that elucidate the lipid composition of complex cellular lysates. The identification of individual lipids within these maps is slow and requires the synthesis and spiking of each candidate lipid. We present a novel MS-based technique that rapidly elucidates the atomic connectivity of the fatty acid/alcohol substituent on the sn-1 position of several different families of glycerophosphocholine-containing lipids within the confines of a chromatographic separation. Sodiated lipid species were fragmented to produce radical cations which lost successive methylene groups upon further collisional activation to reveal the identity of the parent molecule. This approach was demonstrated to be effective on isobaric members of the lysophosphatidylcholine (LPC) and platelet activating factor (PAF) families of glycerophospholipids. We demonstrate the application of this technique to unambiguously identify these species within complex cellular lysates and tissue extracts.