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In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs relatively poorly. To accurately identify radar targets in such scenarios, a novel algorithm, namely YOSMR, based on the deep convolutional network, is proposed. The YOSMR uses the MobileNetV3(Large) network to extract ship imaging data of diverse depths and acquire feature data of various ships. Meanwhile, taking into account the issue of feature suppression for small-scale targets in algorithms composed of deep convolutional networks, the feature fusion module known as PANet has been subject to a lightweight reconstruction leveraging depthwise separable convolutions to enhance the extraction of salient features for small-scale ships while reducing model parameters and computational complexity to mitigate overfitting problems. To enhance the scale invariance of convolutional features, the feature extraction backbone is followed by an SPP module, which employs a design of four max-pooling constructs to preserve the prominent ship features within the feature representations. In the prediction head, the Cluster-NMS method and α-DIoU function are used to optimize non-maximum suppression (NMS) and positioning loss of prediction boxes, improving the accuracy and convergence speed of the algorithm. The experiments showed that the recall, accuracy, and precision of YOSMR reached 0.9308, 0.9204, and 0.9215, respectively. The identification efficacy of this algorithm exceeds that of various YOLO algorithms and other lightweight algorithms. In addition, the parameter size and calculational consumption were controlled to only 12.4 M and 8.63 G, respectively, exhibiting an 80.18% and 86.9% decrease compared to the standard YOLO model. As a result, the YOSMR displays a substantial advantage in terms of convolutional computation. Hence, the algorithm achieves an accurate identification of ships with different trail features and various scenes in marine radar images, especially in different interference and extreme scenarios, showing good robustness and applicability. [ABSTRACT FROM AUTHOR]

Based on a constant volume combustion chamber, the initial ambient pressure effect on gasoline combustion performance and flame propagation of the active and passive pre-chamber ignition systems were studied. Compared with the passive pre-chamber, the active pre-chamber can significantly expand the lean combustion limit from 1.2 to 1.5, enhance the ignition and combustion performance, and speed up the combustion of the main combustion chamber. At slightly lean combustion conditions, the heat release performance has a positive correlation with the initial ambient pressure. As the premixed λ increases, the heat release performance and the initial ambient pressure begin to become negatively correlated. Ignition delay can be decreased by approximately 50% at an initial pressure of 0.75 MPa, premixed lambda of 1.2 with APC compared with PPC. The high ambient pressure (1.0 MPa) in the constant volume chamber greatly reduces the mixture entrainment ability of the jet flame at lean combustion conditions, thereby reducing the combustion speed and peak heat release rate. [ABSTRACT FROM AUTHOR]

In high-traffic harbor waters, marine radar frequently encounters signal interference stemming from various obstructive elements, thereby presenting formidable obstacles in the precise identification of ships. To achieve precise pixel-level ship identification in the complex environments, a customized neural network-based ship segmentation algorithm named MrisNet is proposed. MrisNet employs a lightweight and efficient FasterYOLO network to extract features from radar images at different levels, capturing fine-grained edge information and deep semantic features of ship pixels. To address the limitation of deep features in the backbone network lacking detailed shape and structured information, an adaptive attention mechanism is introduced after the FasterYOLO network to enhance crucial ship features. To fully utilize the multi-dimensional feature outputs, MrisNet incorporates a Transformer structure to reconstruct the PANet feature fusion network, allowing for the fusion of contextual information and capturing more essential ship information and semantic correlations. In the prediction stage, MrisNet optimizes the target position loss using the EIoU function, enabling the algorithm to adapt to ship position deviations and size variations, thereby improving segmentation accuracy and convergence speed. Experimental results demonstrate MrisNet achieves high recall and precision rates of 94.8% and 95.2%, respectively, in ship instance segmentation, outperforming various YOLO and other single-stage algorithms. Moreover, MrisNet has a model parameter size of 13.8M and real-time computational cost of 23.5G, demonstrating notable advantages in terms of convolutional efficiency. In conclusion, MrisNet accurately segments ships with different spot features and under diverse environmental conditions in marine radar images. It exhibits outstanding performance, particularly in extreme scenarios and challenging interference conditions, showcasing robustness and applicability. [ABSTRACT FROM AUTHOR]

The real-time light curve classification of transients is helpful in searching for rare transients. We propose a new algorithm based on machine learning, namely the Temporary Convective Network and Light Gradient Boosting Machine Combined with Weight Module Algorithm (TLW). The TLW algorithm can classify the photometric simulation transients data in g, r, i bands provided via PLAsTiCC, typing Tidal Disruption Event (TDE), Kilonova (KN), Type Ia supernova (SNIa), and Type I Super-luminous supernova (SLSN-I). When comparing the real-time classification results of the TLW algorithm and six other algorithms, such as Rapid, we found that the TLW algorithm has the best comprehensive performance indexes and has the advantages of high precision and high efficiency. The average accuracy of TLW is 84.54%. The average implementation timings of the TLW algorithm for classifying four types of transients is 123.09 s, which is based on TensorFlow's architecture in windows and python. We use three indicators to prove that the TLW algorithm is superior to the classical Rapid algorithm, including Confusion Matrix, PR curve, and ROC curve. We also use the TLW algorithm to classify ZTF real transients. The real-time classification results for ZTF transients show that the accuracy of the TLW algorithm is higher than the other six algorithms. [ABSTRACT FROM AUTHOR]

All-optical radio-frequency spectrum analyzers (AORFSAs) with ultrabroad bandwidth break the electronic bottleneck and provide an efficient frequency analysis means for ultrafast optical signals in communications, signal generation and processing systems. Here, we propose and experimentally demonstrate an AORFSA built on the cross-phase modulation effect in a 50 cm long CMOS-compatible photonic slot-waveguide. The waveguide has a 100 nm thick thin-film core of fused silica that is sandwiched by two 750 nm thick cladding layers of high-index doped silica, which shows optimized dispersion and comparable nonlinear characteristics. The measured 3 dB bandwidth of the proposed slot-waveguide-based AORFSA has a three-fold increase over the conventional channel waveguide having the same dimension and length. The sensitivity and wavelength- and polarization-dependence properties are investigated, confirming the proposed waveguide as a versatile platform for frequency analysis of ultrafast optical signals, such as Kerr microcombs with hundreds of GHz or even THz mode spacing. [ABSTRACT FROM AUTHOR]

Atmospheric drag is an important influencing factor in precise orbit determination and the prediction of low-orbit space debris. It has received widespread attention. Currently, calculating atmospheric drag mainly relies on different atmospheric density models. This experiment was designed to explore the impact of different atmospheric density models on the orbit prediction of space debris. In the experiment, satellite laser ranging data published by the ILRS (International Laser Ranging Service) were used as the basis for the precise orbit determination for space debris. The prediction error of space debris orbits at different orbital heights using different atmospheric density models was used as a criterion to evaluate the impact of atmospheric density models on the determination of space-target orbits. Eight atmospheric density models, DTM78, DTM94, DTM2000, J71, RJ71, JB2006, MSIS86, and NRLMSISE00, were compared in the experiment. The experimental results indicated that the DTM2000 atmospheric density model is best for determining and predicting the orbits of LEO (low-Earth-orbit) targets. [ABSTRACT FROM AUTHOR]

Initial orbit determination (IOD), as a basis for initial orbit association and accurate orbit determination (OD), has a crucial role in the process of obtaining space debris orbit information. Among the traditional methods, the Gooding method has better convergence and stability. In this study, the Gooding method is enhanced to solve the issues discovered. A novel initial orbit determination (IOD) method is developed using the proposed improvement measures of the single-parameter initial value determination (SIVD) method, the fitted-curve noise suppression method, the restricted corrective value solution method, the removal of trivial solutions, etc. The experimental results verify the effectiveness of the improved method. The success rate of the initial orbit determination reached 99%, and the accuracy of the solved orbit parameters was significantly improved, especially the semi-major axis (SMA) error of less than 50 km, accounting for 88% of the total. It can be seen that the method meets the demand of space-based space debris cataloging for initial orbit association and can serve in the field of space situational awareness, which has important practical significance and application potential. [ABSTRACT FROM AUTHOR]

Obesity has become a major health problem worldwide, and increasing evidence supports the importance of microRNAs (miRNAs) in its pathogenesis. Recently, we found that miR-383-5p_1 is highly expressed in the perirenal fat of high-fat-fed rabbits, but it is not yet known whether miR-383-5p is involved in lipid metabolism. Here, we used transcriptome sequencing technology to screen 1642 known differentially expressed genes between miR-383-5p mimic groups and miR-383-5p negative control groups. Gene Ontology Resource (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched in the pathway related to lipid metabolism, and glycine biosynthesis, the NOD receptor signal pathway and nonalcoholic fatty liver were significantly enriched. Afterwards, our research results indicated that miR-383-5p can promote the proliferation and differentiation of rabbit preadipocytes, and there is a direct targeting relationship with RAD51AP1. Mechanistically, miR-383-5p directly interacts with the lipid metabolism and participates in adipogenesis and lipid accumulation by targeting RAD51AP1. In conclusion, our data highlight a physiological role for miRNA in lipid metabolism and suggest the miR-383-5p/RAD51AP1 axis may represent a potential mechanism for controlling lipid accumulation in obesity. [ABSTRACT FROM AUTHOR]

Atmospheric drag is an important factor affecting orbit determination and prediction of low-orbit space debris. To obtain accurate ballistic coefficients of space debris, we propose a calculation method based on measured optical angles. Angle measurements of space debris with a perigee height below 1400 km acquired from a photoelectric array were used for orbit determination. Perturbation equations of atmospheric drag were used to calculate the semi-major-axis variation. The ballistic coefficients of space debris were estimated and compared with those published by the North American Aerospace Defense Command in terms of orbit prediction error. The 48 h orbit prediction error of the ballistic coefficients obtained from the proposed method is reduced by 18.65% compared with the published error. Hence, our method seems suitable for calculating space debris ballistic coefficients and supporting related practical applications. [ABSTRACT FROM AUTHOR]

In previous works, inverse design methods have primarily focused on manipulating the optical power to achieve specific design targets. In this paper, we use the inverse design method to enable the precise engineering of the optical phase. As a proof of concept, we present a series of phase shifters (PSs) with varying phase shifts, which are inversely designed and theoretically validated on the silicon-on-insulator (SOI) platform. The designed PSs exhibit remarkable accuracy, with deviations of below 1 ° . These proposed PSs feature an ultra-compact footprint of 3 µm in length and offer superior fabrication tolerances compared to conventional structures. Over the 1535–1565 nm bandwidth, the discrepancy between the actual and target phase shifts remains below ±1 ° for all phase shifters, while the insertion loss is consistently below 0.035 dB. Moreover, the feasibility of the designed five PSs is verified using 2 × 2 multimode interference couplers (MMI). [ABSTRACT FROM AUTHOR]

Simple Summary: An imbalance of the gut microbiota composition may lead to several reproductive disorders and physiological diseases during pregnancy. This study investigates the fecal microbiome composition between primiparous and multiparous cows during non-pregnancy and pregnancy to analyze the host-microbial balance at different stages. The results indicate that host-microbial interactions promote adaptation to pregnancy and will benefit the development of probiotics or fecal transplantation for treating dysbiosis and preventing disease development during pregnancy. Imbalances in the gut microbiota composition may lead to several reproductive disorders and diseases during pregnancy. This study investigates the fecal microbiome composition between primiparous and multiparous cows during non-pregnancy and pregnancy to analyze the host-microbial balance at different stages. The fecal samples obtained from six cows before their first pregnancy (BG), six cows during their first pregnancy (FT), six open cows with more than three lactations (DCNP), and six pregnant cows with more than three lactations (DCP) were subjected to 16S rRNA sequencing, and a differential analysis of the fecal microbiota composition was performed. The three most abundant phyla in fecal microbiota were Firmicutes (48.68%), Bacteroidetes (34.45%), and Euryarchaeota (15.42%). There are 11 genera with more than 1.0% abundance at the genus level. Both alpha diversity and beta diversity showed significant differences among the four groups (p < 0.05). Further, primiparous women were associated with a profound alteration of the fecal microbiota. The most representative taxa included Rikenellaceae_RC9_gut_group, Prevotellaceae_UCG_003, Christensenellaceae_R_7_group, Ruminococcaceae UCG-005, Ruminococcaceae UCG-013, Ruminococcaceae UCG-014, Methanobrevibacter, and [Eubacterium] coprostanoligenes group, which were associated with energy metabolism and inflammation. The findings indicate that host-microbial interactions promote adaptation to pregnancy and will benefit the development of probiotics or fecal transplantation for treating dysbiosis and preventing disease development during pregnancy. [ABSTRACT FROM AUTHOR]

The standard silicon photonic platforms provide three-step silicon etching, i.e., 220 nm for full etching, 70 nm for shallow etching, and 130 nm (or 150 nm) for slab etching. Previously reported mode-evolution-based polarization rotators and splitters (PSRs) usually employ 130 nm-etched slab waveguides for adiabatic TM 0 -to-TE 1 conversion, however, they are not compatible with the platforms adopting 150 nm-etching techniques. In this paper, we demonstrate a broadband PSR based on 70 nm-etched slab waveguides, which is compatible with all the platforms. The PSR consists of a bi-level taper and an inverse-tapered coupler. The length of the polarization rotator shrinks from hundreds to only thirty microns by employing the 70 nm-etched slab waveguides, while a high efficiency of >95% is achieved, covering an ultra-wide bandwidth from 1250 nm to 1650 nm. The proposed PSR shows superior performance over S, C, and L bands. Low cross-talk of <−20 dB and a loss of <1.5 dB are experimentally confirmed over a wavelength range of 75 nm. [ABSTRACT FROM AUTHOR]

We designed a structure of dual-coupled ridge waveguide in thin-film lithium-niobate-on-insulator (LNOI) and numerically studied the highly efficient, broadband, and flattened dispersive wave-enhanced supercontinuum generation in the mid-infrared region. By leveraging the mode coupling of the proposed dual-coupled waveguide structure, one of the supermodes, namely the anti-symmetric mode, can produce additional zero-dispersion wavelengths in the mid-infrared region, and consequently multiple normal dispersion regions for dispersive wave emission. Given the rich geometrical degrees of freedom powered by this dual-coupled LNOI waveguide structure, we can tailor the dispersion profile so that a well-established mode-locked fiber laser in the telecommunication band can serve as the pump. Thus, the whole system can potentially be fiber-to-chip integrated and packaged, enabling a compact, cost-effective, and low system-complexity platform. We numerically show that the broadband dispersive wave covering the wavelength range of 1.92~3.55 μ m (−20 dB level, near octave-spanning) with spectral flatness of 6.31 dB can be achieved using a 1550 nm, 190 pJ femtosecond pump seed. When the dual hump-shaped spectrum is obtained, the conversion efficiency of the mid-infrared dispersive wave can be up to 19.31%. The influence of the pumping conditions on the performance of mid-infrared dispersive wave generation was also studied. This work provides a competitive candidate for efficient, broadband, and flattened mid-infrared spectrum generation, which can find important applications in spectroscopy, metrology, and communication. [ABSTRACT FROM AUTHOR]

For the requirements of rigorous CO2 and emissions regulations, steam assist technology is an effective method for thermal efficiency enhancement. However, few studies apply steam assist technology in modern internal combustion engines. Stimulated by its application prospects, the present study proposes a thermodynamic analysis on the in-cylinder steam assist technology. An ideal engine thermodynamic model combined with a heat exchanger model is established. Some critical parameters, such as steam injection temperature, injection pressure and intake pressure, are calculated under different steam injection masses. The thermal efficiency boundaries are also analyzed at different compression ratios to investigate the maximum potential thermal efficiency of the technology. The analysis shows that the in-cylinder steam-assisted cycle has the potential to increase engine efficiency considerably. Both steam injection temperature and injection mass improve thermal efficiency. Considering the energy trade-off relationship between steam and exhaust gas, the maximum gain in thermal efficiency achieved with the cycle is 14.5% at a compression ratio of 10. The optimum thermal efficiency can be increased from 54.0% to 59.71% by increasing the compression ratio from 10 to 16. The mechanism lies in the specific heat ratio enhancement from a thermodynamic perspective, which improves the thermal-heat conversion efficiency. The results provide considerable guidance for the future experimental and numerical studies of in-cylinder steam assist technology into modern engines. [ABSTRACT FROM AUTHOR]

Simple Summary: In July 2020, China completely banned the addition of antibiotics to feed, which had a huge impact on animal husbandry, such as the increased incidence of some intestinal diseases. In this study, the pathogenesis of diarrhea in rabbits fed with antibiotic-free diet was studied by multi-omics analysis. The study found that the relative abundances of Firmicutes and Proteobacteria in the cecum of diarrhea-afflicted rabbits changed significantly. Most of the differential expression genes identified were related to cecum inflammation and immune response, and a total of 652 differential metabolites were identified, mainly involved in inflammation-related metabolic pathways such as bile secretion, folic acid resistance, and tryptophan metabolism. In addition, Fournierella was positively correlated with myricetin and ursolic acid; thus, it might further cause bile secretion and tryptophan metabolism disorders, aggravate intestinal inflammation, change intestinal permeability, reduce host immunity, and lead to diarrhea in rabbits. With the comprehensive prohibition of antibiotics in the feed industry in China, the incidence of diarrhea in rabbits increased, such as loss of appetite, vomiting, and excretion of atheromatous feces. In order to explore the pathological and the molecular mechanisms of the diarrhea in the rabbitry fed with antibiotic-free diet, we used microbial metagenomics, transcriptome, and non-targeted metabolomics sequencing. The results showed that the Firmicutes level was significantly decreased (p < 0.001) and the Proteobacteria level was significantly increased (p < 0.05). The functional enrichment of cecum revealed that most differentially expressed genes (DEGs) were expressed in immune, inflammatory, and metabolic processes. The enrichment of the cecal fecal metabolites focused on the bile secretion, antifolate resistance, and tryptophan metabolism pathways, which are mainly associated with inflammation. The results of correlation analysis showed that Fournierella was positively correlated with myricetin, ursolic acid, and furtherly might cause bile secretion and tryptophan metabolism disorder, aggravate intestinal inflammation, change intestinal permeability, and reduce host immunity, leading to diarrhea in rabbits. This study provides a theoretical basis for illustrating the reason for diarrhea and developing new feeds for the health of rabbits. [ABSTRACT FROM AUTHOR]

In order to obtain the expressions of RMS position error, we have to derive the expressions of HT ht and HT ht . Similarly, HT ht , HT ht are the LOS vector errors in the topocentric coordinate systems. The actual position of space debris is denoted by T. HT ht and HT ht are the LOS vector errors in the topocentric coordinate systems. [Extracted from the article]

A single electro-optical (EO) sensor used in space debris observation provides angle-only information. However, space debris position can be derived using simultaneous optical measurements obtained from two EO sensors located at two separate observation sites, and this is commonly known as triangulation. In this paper, we propose a new triangulation algorithm to determine space debris position, and its analytical expression of Root-Mean-Square (RMS) position error is presented. The simulation of two-site observation is conducted to compare the RMS positioning error of the proposed triangulation algorithm with traditional triangulation algorithms. The results show that the maximum RMS position error of the proposed triangulation algorithm is not more than 200 m, the proposed triangulation algorithm has higher positioning accuracy than traditional triangulation algorithms, and the RMS position error obtained in the simulation is nearly consistent with the analytical expression of RMS position error. In addition, initial orbit determination (IOD) is carried out by using the triangulation positioning data, and the results show that the IOD accuracy of two-site observation is significantly higher than that of the single-site observation. [ABSTRACT FROM AUTHOR]

Mode-order converters drive the on-chip applications of multimode silicon photonics. Here, we propose a TM0-to-TM3 mode-order converter by leveraging a shallowly etched slot metasurface pattern atop the silicon waveguide, rather than as some previously reported TE-polarized ones. With a shallowly etched pattern on the silicon waveguide, the whole waveguide refractive index distribution and the corresponding field evolution will be changed. Through further analyses, we have found the required slot metasurface pattern for generating the TM3 mode with high conversion efficiency of 92.9% and low modal crosstalk <−19 dB in a length of 17.73 μm. Moreover, the device's working bandwidth and the fabrication tolerance of the key structural parameters are analyzed in detail. With these features, such devices would be beneficial for the on-chip multimode applications such as mode-division multiplexing transmission. [ABSTRACT FROM AUTHOR]

The internal combustion Rankine cycle (ICRC) concept provides a potential solution for future high thermal efficiency and low emission powertrains, and direct water injection (DWI) proved to be the key parameter for ICRC optimization. This paper was dedicated to investigating the fundamental mechanisms of water spray characteristics under different water injection control parameters. In order to do so, an experimental test system was carefully designed and built based on the Bosch and Schlieren methods: the Bosch method is utilized to measure the effect of injection and ambient pressure on water injection characteristics, and the Schlieren method is utilized to investigate the impact of water injection and ambient temperature on water spray and evaporation processes. The experimental results indicate that both control parameters show important effects on water injection and spray characteristics. The water injection and ambient pressure show significant impacts on steady-state flow quantity and cyclic water injection quantity, and the water injection and ambient pressure affect the evaporation ability of water vapor within the spray which leads to a different variation trend during the initial, developing, and developed water spray stages. The results of this work can be used as fundamental supplements for ICRC, steam assistant technology (SAT), and DWI-related ICEs experimental and numerical researches, and provide extra information to understand the DWI process within engine-relevant conditions. [ABSTRACT FROM AUTHOR]

The monotonic work function of graphene makes it difficult to meet the electrode requirements of every device with different band structures. Two-dimensional (2D) transition metal carbides (TMCs), such as carbides in MXene, are considered good candidates for electrodes as a complement to graphene. Carbides in MXene have been used to make electrodes for use in devices such as lithium batteries. However, the small lateral size and thermal instability of carbides in MXene, synthesized by the chemically etching method, limit its application in optoelectronic devices. The chemical vapor deposition (CVD) method provides a new way to obtain high-quality ultrathin TMCs without functional groups. However, the TMCs film prepared by the CVD method tends to grow vertically during the growth process, which is disadvantageous for its application in the transparent electrode. Herein, we prepared an ultrathin Mo2C—graphene (Mo2C—Gr) hybrid film by CVD to solve the above problem. The work function of Mo2C—Gr is between that of graphene and a pure Mo2C film. The Mo2C—Gr hybrid film was selected as a transparent hole-transporting layer to fabricate novel Mo2C—Gr/Sb2S0.42Se2.58/TiO2 two-sided photodetectors. The Mo2C—Gr/Sb2S0.42Se2.58/TiO2/fluorine-doped tin oxide (FTO) device could detect light from both the FTO side and the Mo2C—Gr side. The device could realize a short response time (0.084 ms) and recovery time (0.100 ms). This work is believed to provide a powerful method for preparing Mo2C—graphene hybrid films and reveals its potential applications in optoelectronic devices. [ABSTRACT FROM AUTHOR]

Polarization-insensitive modulation, i.e., overcoming the limit of conventional modulators operating under only a single-polarization state, is desirable for high-capacity on-chip optical interconnects. Here, we propose a hybrid graphene-silicon-based polarization-insensitive electro-absorption modulator (EAM) with high-modulation efficiency and ultra-broad bandwidth. The hybrid graphene-silicon waveguide is formed by leveraging multi-deposited and multi-transferred methods to enable light interaction with graphene layers in its intense field distribution region instead of the commonly used weak cladding region, thus resulting in enhanced light–graphene interaction. By optimizing the dimensions of all hybrid graphene-silicon waveguide layers, polarization-insensitive modulation is achieved with a modulation efficiency (ME) of ~1.11 dB/µm for both polarizations (ME discrepancy < 0.006 dB/µm), which outperforms that of previous reports. Based on this excellent modulation performance, we designed a hybrid graphene-silicon-based EAM with a length of only 20 µm. The modulation depth (MD) and insertion loss obtained were higher than 22 dB and lower than 0.23 dB at 1.55 µm, respectively, for both polarizations. Meanwhile, its allowable bandwidth can exceed 300 nm by keeping MD more than 20 dB and MD discrepancy less than 2 dB, simultaneously, and its electrical properties were also analyzed. Therefore, the proposed device can be applied in on-chip optical interconnects. [ABSTRACT FROM AUTHOR]