Deep Learning Based Underwater Acoustic Target Recognition: Introduce a Recent Temporal 2D Modeling Method.

In recent years, the application of deep learning models for underwater target recognition has become a popular trend. Most of these are pure 1D models used for processing time-domain signals or pure 2D models used for processing time-frequency spectra. In this paper, a recent temporal 2D modeling method is introduced into the construction of ship radiation noise classification models, combining 1D and 2D. This method is based on the periodic characteristics of time-domain signals, shaping them into 2D signals and discovering long-term correlations between sampling points through 2D convolution to compensate for the limitations of 1D convolution. Integrating this method with the current state-of-the-art model structure and using samples from the Deepship database for network training and testing, it was found that this method could further improve the accuracy (0.9%) and reduce the parameter count (30%), providing a new option for model construction and optimization. Meanwhile, the effectiveness of training models using time-domain signals or time-frequency representations has been compared, finding that the model based on time-domain signals is more sensitive and has a smaller storage footprint (reduced to 30%), whereas the model based on time-frequency representation can achieve higher accuracy (1-2%).

Simultaneous bond-selective deuterium-based isotopic labeling sensing with disposable ultra-miniature CARS fiber probe.

Deuterium-based isotopic labeling is an important technique for tracking cellular metabolism with the Raman signals analysis of low-wavenumber (LW) C-D bonds and high-wavenumber (HW) C-H bonds. We propose and demonstrate a disposable ultra-miniature fiber probe to detect LW and HW coherent anti-Stokes Raman scattering (CARS) spectra for deuterated compounds simultaneously and bond-selectively sensing. The 10.78 µm diameter disposable fiber probe, comprised of focusing taper as fiber probe head and time-domain walk-off eliminating fiber section with designed length, realizes wide-frequency-interval dual Stokes pulse delivering and focusing. The fiber probe enables quantitative concentration determination with resolution down to 11 mM. The chemical vibration modes of LW region C-D bonds and HW region C-H bonds of the mixture samples of organic compounds and their deuterated counterparts in a simulated cell are simultaneously excited and characterized. The CARS disposable fiber probe introduces a promising handle for in vivo biochemical detection based on isotopic labeling sensing.

The neuromodulatory effects of flavonoids and gut Microbiota through the gut-brain axis.

Recent investigations show that dietary consumption of flavonoids could potentially confer neuroprotective effects through a variety of direct and indirect mechanisms. Numerous flavonoids have been shown to cross the BBB and accumulate within the central nervous system (CNS). Some of these compounds purportedly counteract the accumulation and deleterious effects of reactive oxygen species, fostering neuronal survival and proliferation by inhibiting neuroinflammatory and oxidative stress responses. Moreover, several studies suggest that gut microbiota may participate in regulating brain function and host behavior through the production and modulation of bioactive metabolites. Flavonoids may shape gut microbiota composition by acting as carbon substrates to promote the growth of beneficial bacteria that produce these neuroprotective metabolites, consequently antagonizing or suppressing potential pathogens. By influencing the microbiota-gut-brain axis through this selection process, flavonoids may indirectly improve brain health. This review examines the current state of research into the relationship between bioactive flavonoids, gut microbiota, and the gut-brain axis.

A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis.

The technology of fault diagnosis helps improve the reliability of wind turbines. Difficulties in feature extraction and low confidence in diagnostic results are widespread in the process of deep learning-based fault diagnosis of wind turbine bearings. Therefore, a probabilistic Bayesian parallel deep learning (BayesianPDL) framework is proposed and then achieves fault classification. A parallel deep learning (PDL) framework is proposed to solve the problem of difficult feature extraction of bearing faults. Next, the weights and biases in the PDL framework are converted from deterministic values to probability distributions. In this way, an uncertainty-aware method is explored to achieve reliable machine fault diagnosis. Taking the fault signal of the gearbox output shaft bearing of a wind turbine generator in a wind farm as an example, the diagnostic accuracy of the proposed method can reach 99.14%, and the confidence in diagnostic results is higher than other comparison methods. Experimental results show that the BayesianPDL framework has unique advantages in the fault diagnosis of wind turbine bearings.

Double-Antibody Sandwich Immunoassay and Plasmonic Coupling Synergistically Improved Long-Range SPR Biosensor with Low Detection Limit.

A long-range surface plasmonic resonance (LR-SPR) biosensor modified with double-antibody sandwich immunoassay and plasmonic coupling is demonstrated for human-immunoglobulin G detection with a low limit of detection (LOD). The double-antibody sandwich immunoassay dramatically changes the average refractive index of the medium layer on the sensor surface. The near-field electron coupling between the localized surface plasmon and the long-range surface plasmon leads to a significant perturbation of the evanescent field. The large penetration depth and the long propagation distance of the long-range surface plasmonic waves facilitate the LR-SPR sensor in the detection of biological macromolecules. The unique light absorption characteristic of the nanocomposite material in the sensor provides the in situ self-compensation for the disturbance. Therefore, besides the inherent advantages of optical fiber sensors, the developed biosensor can realize the detection of biomolecules with high sensitivity, low LOD and high accuracy and reliability. Experimental results demonstrate that the LOD of the biosensor is as low as 0.11 µg/mL in the detection of the phosphate-buffered saline sample, and the spike-and-repetition rate is 105.56% in the detection of the real serum sample, which partly shows the practicability of the biosensor. This indicates that the LR-SPR biosensor provides better response compared with existing similar sensors and can be regarded as a valuable method for biochemical analysis and disease detection.

Refractometric Sensitivity Enhancement of Weakly Tilted Fiber Bragg Grating Integrated with Black Phosphorus.

The sensitivity enhancement of the weakly tilted fiber Bragg grating (WTFBG) integrated with black phosphorus (BP) was investigated via numerical simulations and experimental demonstrations. BP nanosheets were deposited twice on the cylindrical WTFBG surface using the in situ layer-by-layer (i-LbL) deposition technique. The resonance intensity of the deepest cladding mode located around 1552 nm of WTFBG had a 9.2 dB decrease after the BP deposition process. This allows for the application of the intensity-modulated refractive index (RI) sensor. The sensing platform was implemented on the use of the BP integrated with WTFBG (BP-WTFBG). The refractometric sensing was achieved with the sensitivity enhancement of the resonance intensity modulation of the deepest cladding mode for the BP-WTFBG. The sensitivities were 137.6 dB/RIU and 75.6 dB/RIU in the RI region of 1.33-1.35 and 1.35-1.38, respectively. This platform shows great potential applications for biochemical sensing because of its highly sensitive RI sensing ability around the biochemical sensing window.

All optic-fiber coupled plasmon waveguide resonance sensor using ZrS2 based dielectric layer.

We developed an all optic-fiber coupled plasmon waveguide resonance (CPWR) sensor using a zirconium disulfide (ZrS2) based dielectric layer. The dielectric constants of ZrS2 were obtained using first-principles calculations. The theoretical model of the proposed sensor was established based on the transfer matrix method, leading to the optimization of the parameters in the sensor. The sensor was fabricated by depositing a gold layer of 35 nm on the fiber core and immobilizing the ZrS2 layer on the gold layer via physical adsorption method. An experimental setup was implemented for measuring the refractive index. The sensor with two cycles showed the best performance, with a sensitivity of higher than 8000 nm/RIU.

Multi-layer optical fiber surface plasmon resonance biosensor based on a sandwich structure of polydopamine-MoSe2@Au nanoparticles-polydopamine.

An all-optical fiber multi-layer surface plasmon resonance (SPR) biosensor based on a sandwich structure of polydopamine-MoSe2@Au nanoparticles-polydopamine (PDA-MoSe2@AuNPs-PDA) was designed for the detection of specific immunoreactions. By optimizing the multi-layer structure and the ratio of MoSe2: AuNPs, a sensitivity of 5117.59 nm/RIU has been obtained, which is more than double that of the only Au-filmed optical fiber SPR sensor. A large surface area was produced by integrating the MoSe2 primitive unit cell and the AuNPs into a hybrid plasmonic nanostructure of MoSe2@AuNPs, leading to optical fiber SPR signal amplification. The nanostructure of MoSe2@AuNPs was surrounded by the PDA layer to guarantee the efficient immobilization of the protein molecules on the optical fiber by strong covalent bond. This biosensor achieved a detection limit of 54.05 ng/mL for detecting the goat-anti-rabbit IgG, which demonstrated enhancements of 12.1%, 23.3% and 184.6% in comparison with three reported SPR biosensors decorated with PDA-AuNPs-PDA, PDA and Cysteamine-MoSe2@AuNPs-Cysteamine nanostructure, respectively. This biosensor achieved favorable selectivity and outstanding sensitivity compared with the reported SPR immuno-sensors, which will provide a miniaturized, rapid-response and label-free optical fiber bio-sensing platform for clinical diagnosis in the future.

Cryo-EM Structure of a Bacterial Lipid Transporter YebT.

The outer membrane (OM) of Gram-negative bacteria is asymmetric, with lipopolysaccharides (LPSs) on the outer surface and phospholipids (PLs) on the inner surface. This unique organization of OM makes Gram-negative bacteria resistant to many toxic chemicals. How this asymmetric distribution of lipids is maintained has been studied for decades with previous reports of an Mla (Maintenance of OM Lipid Asymmetry) system to be involved. Furthermore, the OM of Gram-negative bacteria is about 20 nm away from inner membrane (IM) where the lipids are synthesized. Therefore, how nascent lipids travel across the periplasmic space and arrive at the inner surface of OM is another interesting question. YebT is a homologue of MlaD in the Mla pathway, but its role in lipid distribution of the OM and IM is largely unknown. Here we report the first high-resolution (~3.0 Å) cryo-EM structure of full-length E. coli YebT in a substrate-bound state. Our structure with details of lipid interaction indicates that YebT is a lipid transporter spanning between IM and OM. We also demonstrate the symmetry mismatch in YebT and the existence of many other conformations of YebT revealing the intrinsic dynamics of this lipid channel. And a brief discussion on possible mechanisms of lipid transport is also included.

Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds.

Comparative population genomics analysis is an effective approach to identify selection signatures in farm animals. In this study, we systematically investigated the selection signatures in six phenotypically diverse goat breeds using SNPs obtained from pooled whole-genome resequencing data. More than 95.5% of 446-642 million clean reads were mapped to the latest reference goat genome, which generated a sequencing depth ranging from 22.30 to 31.75-fold for each breed. A total of 5,802,307, 6,794,020, 7,562,312, 5,325,119, 8,764,136, and 9,488,057 putative SNPs were detected in Boer, Meigu, Jintang Black, Nanjiang Yellow, Tibetan, and Tibetan cashmere goats, respectively. Based on the genome-wide FST and expected heterozygosity scores along 100-kb sliding windows, 68, 89, 44, 44, 19, and 35 outlier windows were deemed as the selection signatures in the six goat breeds. After genome annotation, several genes within the selection signals were found to be possibly associated with important traits in goats, such as coat color (IRF4, EXOC2, RALY, EIF2S2, and KITLG), high-altitude adaptation (EPAS1), growth (LDB2), and reproduction traits (KHDRBS2). In summary, we provide an improved understanding of the genetic diversity and the genomic footprints under positive selection or the adaptations to the local environments in the domestic goat genome.

Enhanced photocatalytic activity of Bi12O17Cl2 nano-sheets via surface modification of carbon nanotubes as electron carriers.

A novel carbon nanotubes modified Bi12O17Cl2 composite (CNTs/Bi12O17Cl2) was prepared via hydrothermal method. The chemical structures, morphologies, optical properties of the synthesized samples were revealed by XRD, XPS, SEM, TEM, BET and UV-vis DRS measurements. The photocatalytic activity of the CNTs/Bi12O17Cl2 composite was evaluated with degradation reaction of rhodamine B (RhB) under visible light. CNTs/Bi12O17Cl2 exhibited improved photocatalytic activity in comparison with pure Bi12O17Cl2, and kept favorable stability and recyclability in the reaction. The relatively high photocatalytic activity of CNTs/Bi12O17Cl2 resulted from the enhanced separation efficiency of photo-induced charges, which were revealed by the photoluminescence spectra and transient photocurrent measurements. CNTs loaded at the surface of Bi12O17Cl2 sheets acted as electron carriers to efficiently transfer the photoinduced electrons, namely to promote the separation of photoinduced electrons and holes, thus improving the photocatalytic activity of the composite materials. At last, a possible photocatalytic reaction mechanism over the CNTs/Bi12O17Cl2 composite was proposed based on the results of trapping experiment, ESR measurements and the band energy analysis.

[Investigation on internal energy transfer and relaxation kinetics of NO2 by photoacoustic and fluorescence emission spectra].

With 532 nm laser as excitation source, the excitation and relaxation process of NO2 molecule was investigated by the technique of photoacoustic and fluorescence emission spectra. The results show that NO2 molecules will be pumped to the first excited electronic state by laser photon. When the sample pressure is lower, some of the excited molecules relax to the ground state by radiation process directly; the other parts are redistributed to a few of the excited rovibronic energy levels by the process of fast internal energy transfer. With the increase in the sample pressure, continual collisions dominate the relaxation process gradually. This makes the excited molecules to be redistributed to many excited rovibronic energy levels. Emission from these excited levels forms a continuous spectrum. Just then, the efficiency of fluorescence emission from laser excited level decreases and the fluorescence intensity on the long wavelength side increases. The intensity of PA signals increases also. These phenomena indicate that besides the relaxation process of radiation, there is a strong relaxation process of continual collision under the condition of higher sample pressure. It converts vibration energy of the excited molecules into translation one. This induces the increase in gas temperature and a sound wave is produced.