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Using a deep learning method to detect buried pipes on ground penetrating radar (GPR) data is popular for its excellent performance potential. However, this needs a large amount of high-quality training data, which leads to time-consuming and labor-intensive data annotation work. Semi-supervised learning method provides a solution for the situation of small sample size. However, the original semi-supervised learning methods lack control over the quality of pseudo labels during model training. To address the problem, a new prior knowledge-guided semi-supervised deep learning method is proposed to improve the model performance under the small sample. In the method, a prior structure feature (PSF) is constructed to control the quality of pseudo label during semi-supervised learning. The structure response index (SRI) is designed to segment the structure subject out for eliminating disturbance from unstructured information. Then, the PSF is represented using histograms of oriented gradients (HOGs) and Fourier descriptors (FDs) to describe the structure’s edge orientation and shape. Based on the PSF, LightGBM is employed as a discriminator to screen out high-quality pseudo labels for model training. In the experiments, comparison experiments with some state-of-the-art supervised learning methods and semi-supervised learning methods were carried out to validate the method’s performance. The ablation studies on labeled dataset size, pseudo-label confidence threshold, and PSF were conducted to validate the effectiveness of the prior structural feature in controlling the pseudo label’s quality. The results show that the PSF is effective, and the proposed method outperforms the other methods.

To improve the efficiency of detecting abnormal traffic incidents on the road network and reduce the false alarm rate, a real-time traffic anomaly detection framework based on a graph spatiotemporal pattern learning (GSTPL) network is proposed. In this framework, a traffic pattern search algorithm based on a fluctuation similarity measure is designed to screen traffic flow data with the same traffic pattern, and a traffic pattern graph tuple is constructed as the input of the network model to avoid the sample imbalance problem and the effect of single-sample randomness for traffic pattern learning. Then the GSTPL network is designed to extract, unsupervised, the traffic spatiotemporal pattern features and make a reasonable prediction of future traffic parameters as the basis for anomaly evaluation. To further restrain the effect of random fluctuations in traffic flow parameters, an abnormal state evaluation method is designed to calculate the anomaly state likelihood by prediction error distribution learning. The overall detection framework realizes stable prediction of network key node traffic parameters by using spatiotemporal pattern features to construct the traffic pattern graph tuple, and gives incident evaluation results in real time by combination with the detection data. The experiment uses I90 and I405 highway traffic data in Seattle, WA, from 2015. Through comparative analysis, the proposed incident detection method based on GSTPL has a higher detection rate and lower false alarm rate, can adaptively learn dynamic changes of the traffic pattern, and has strong adaptability and stability to different traffic environments.

A green economic transformation requires innovation in related technologies. The impact of digitalization on corporate green innovation must be investigated in the context of increasing policy uncertainty; therefore, this study uses data from listed manufacturing enterprises in China from 2011 to 2020, constructs a digitization and policy uncertainty perception index based on text analysis, and investigates corporate green technology innovation in light of digitization and policy uncertainty perception. The results indicate that digitization substantially and positively affects corporate green technology innovation, which raises its performance. An array of robustness tests, including instrumental variable methods, supports the conclusion that digitization enables green innovation. A Heterogeneity analysis also indicates that digitization has a pronounced impact on green technology innovation in large, capital-intensive, and state-owned enterprises. Frequent policy adjustment engenders an upsurge in policy uncertainty, which impedes corporate green technology innovation; however, digitization can play a vital role in alleviating the negative impacts of economic policy uncertainty, thereby accelerating the development of corporate green technologies. This article provides empirical evidence on achieving green and sustainable development in the digital era, making a valuable contribution to the existing literature.

Pavement segregation reduces pavement strength and causes early pavement damage. As a convenient and nondestructive subsurface detection technology, ground penetrating radar (GPR) is widely applied to detect segregation by manual interpretation. This induces labor-intensive and time-consuming. And then the segregation is interpreted automatically by image processing technology based on GPR B-scan images. However, this ignores the intrinsic physical properties of segregation. To address the problem, a new method for automatically detecting segregation is proposed to interpret segregation by combining visual features with intrinsic physical properties of segregation. In the method, GPR data preprocessing is carried out to remove the subgrade layer disturbance and enhance the GPR signal. And then the candidate segregation locating is put forward by the segregation representation index (SRI) and graph cuts algorithm according to segregation visual and statistical characteristics. Segregation visual features and intrinsic physical properties are represented for recognition according to gray-level co-occurrence matrix (GLCM) and dielectric properties. Extreme gradient boosting (XGBoost) is employed as a classifier to recognize segregation. In experiments, experiment samples are collected by 3-D GPR testing vehicle and coring experiments, and comparison experiments are carried out to validate the proposed method by analysis on feature selection, segregation localization, and segregation recognition. The results show the proposed method has a better performance than the other methods, such as multigrained cascade forest (gcForest), deepLab v3+, and SegNet. As a result, the proposed method will provide a new reference for automatic interpretation GPR application, especially, on the combining visual features with intrinsic physical properties.

In this work, a dual-band junction field effect phototransistor (JFEPT) was fabricated by integrating p-type black phosphorus (BP) with Si-doped $\beta $ -Ga2O3. The operation principle of the JFEPT was systematically investigated by commercial TACD software SILVACO. The results indicate that the photocurrent is mainly formed by electrons under short-wave radiation, while it is composed of electrons and holes under long-wave irradiation. In addition, the Ga2O3 doping concentration was determined to be $3\times 10^{{16}}$ cm $^{-{3}}$ to obtain a large photo-to-dark current ratio (PDCR). The threshold voltage ( ${V}_{\text {th}}{)}$ of the fabrication JFEPT was 0.65 V, indicating that the device working in normally- OFF state. The drain current was $\sim 10^{-{6}}$ mA/mm and the ON/ OFF ratio is $10^{{5}}$ at ${V}_{G}$ = −4 V and ${V}_{\text {DS}}$ = 5 V. And the device exhibits a low leakage current of $2.84\times 10^{-{6}}$ mA/mm. Under 254- and 808-nm illumination, the PDCR were 14713.79 and 5.53, and the responsivity was calculated to be $2.39\times 10^{{6}}$ and 535 mA/W, respectively. In addition, a low noise current of 0.17 nA/Hz $^{\text {1/{2}}}$ at 1 Hz is beneficial for the device to detect the ultraweak optical signal. This work provides an important reference for the realization of high-performance UV-IR dual-band detector.

High-performance $\beta $ -Ga2O3 U-shaped trench-gate metal-oxide-semiconductor field-effect transistor (UMOSFET) has been demonstrated. Nitrogen ions implantation was employed to form current blocking layer. Electrons in the blocking layer can accumulate in the area near the U-shaped groove and form a conductive channel to promote current generation at a positive gate bias. The UMOSFET with an applicable threshold voltage of 4.2 V was achieved by modulating the concentration of implanted nitrogen ions. A high current density of 702.3 A/cm2, a low on-resistance of 10.4 $\text{m}\Omega \cdot $ cm2, and a decent breakdown voltage of 455 V (at ${V}_{\text {G}}=0$ V) were obtained for UMOSFET with N ions concentration of ${5}\times {10} ^{{18}}$ cm $^{-{3}}$ . The UMOSFET in this work offers exceptional advantages in fabrication of high-performance E-mode vertical $\beta $ -Ga2O3 MOSFETs, facilitating the development of $\beta $ -Ga2O3 power electronics devices.

In this paper, self-powered ultraviolet (UV) photodetectors with high response performance based on Ga2O3/p-GaN were fabricated by metal–organic chemical vapor deposition (MOCVD). The effects of different crystal phases of Ga2O3(including a, ε, ε/β, and β) grown on p-GaN films on the performance of photodetectors were systematically studied. Moreover, an in situGaON dielectric layer improved the responsivity of Ga2O3/p-GaN photodetectors by 20 times. All Ga2O3/p-GaN photodetectors showed self-power capability without bias. An ultralow dark current of 3.08 pA and a Iphoto/Idarkratio of 4.1 × 103(1.8 × 103) under 254 nm (365 nm) light were obtained for the β-Ga2O3/p-GaN photodetector at 0 V bias. Furthermore, the β-Ga2O3/p-GaN photodetector showed excellent sensitivity with a high responsivity of 3.8 A/W (0.83 A/W), a fast response speed of 66/36 ms (36/73 ms), and a high detectivity of 1.12 × 1014Jones (2.44 × 1013Jones) under 254 nm (365 nm) light at 0 V bias. The carrier transport mechanism of the Ga2O3/p-GaN self-powered photodetector was also analyzed through the device energy band diagram. This work provides critical information for the design and fabrication of high-performance self-powered Ga2O3/p-GaN UV photodetectors, opening the door to a variety of photonic systems and applications without an external power supply.

The use of two inhibitors of Mek1/2 and Gsk3β (2i) promotes the generation of mouse diploid and haploid embryonic stem cells (ESCs) from the inner cell mass of biparental and uniparental blastocysts, respectively. However, a system enabling long-term maintenance of imprints in ESCs has proven challenging. Here, we report that the use of a two-step a2i (alternative two inhibitors of Src and Gsk3β, TSa2i) derivation/culture protocol results in the establishment of androgenetic haploid ESCs (AG-haESCs) with stable DNA methylation at paternal DMRs (differentially DNA methylated regions) up to passage 60 that can efficiently support generating mice upon oocyte injection. We also show coexistence of H3K9me3 marks and ZFP57 bindings with intact DMR methylations. Furthermore, we demonstrate that TSa2i-treated AG-haESCs are a heterogeneous cell population regarding paternal DMR methylation. Strikingly, AG-haESCs with late passages display increased paternal-DMR methylations and improved developmental potential compared to early-passage cells, in part through the enhanced proliferation of H19-DMR hypermethylated cells. Together, we establish AG-haESCs that can long-term maintain paternal imprints.

The E3 ligase TRIM7 has emerged as a critical player in viral infection and pathogenesis. However, the mechanism governing the TRIM7–substrate association remains to be defined. Here we report the crystal structures of TRIM7 in complex with 2C peptides of human enterovirus. Structure-guided studies reveal the C-terminal glutamine residue of 2C as the primary determinant for TRIM7 binding. Leveraged by this finding, we identify norovirus and SARS-CoV-2 proteins, and physiological proteins, as new TRIM7 substrates. Crystal structures of TRIM7 in complex with multiple peptides derived from SARS-CoV-2 proteins display the same glutamine-end recognition mode. Furthermore, TRIM7 could trigger the ubiquitination and degradation of these substrates, possibly representing a new Gln/C-degron pathway. Together, these findings unveil a common recognition mode by TRIM7, providing the foundation for further mechanistic characterization of antiviral and cellular functions of TRIM7.

Four ionic liquids, 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]), 1-butyl-3-methylimidazolium acetate ([BMIM][OAc]), 1-hexyl-3-methylimidazolium acetate ([HMIM][OAc]), and 1-octyl-3-methylimidazolium acetate ([OMIM][OAc]), were used to swell Hefeng sub-bituminous coal. The effect of swelling on the molecular structure and pyrolysis behavior of the coal was investigated by swelling degree Q, SEM, FTIR, and TG-DTG characterizations. Results showed that swelling degree by different ionic liquid was in the range of 2.0–2.4, with a higher degree of 2.4 for the coal sample swelled by [OMIM][OAc]. The swelling process could destroy the surface morphology and pore structure of the coal and increase and loosen the sample’s pore channel. The results of the FTIR analysis revealed that swelling can destroy hydrogen bonds in coal, reduce the relative content of oxygen-containing functional groups, and might increase the relative amount of low-molecular-weight organics. TG-DTG profiles proposed that swelling with ionic liquid could promote weight loss and pyrolysis conversion of the coal and significantly changed its pyrolysis behavior at the temperature of 180–350 °C. The Coats–Redfern results presented that swelling increased the pyrolysis activation energy of the coal at 180–350 °C, while the energy was decreased at 350–550 °C.

Multisystem manifestations in myotonic dystrophy type 1 (DM1) may be due to dosage reduction in multiple genes induced by aberrant expansion of CTG repeats in DMPK, including DMPK, its neighboring genes (SIX5or DMWD) and downstream MBNL1. However, direct evidence is lacking. Here, we develop a new strategy to generate mice carrying multigene heterozygous mutations to mimic dosage reduction in one step by injection of haploid embryonic stem cells with mutant Dmpk, Six5and Mbnl1into oocytes. The triple heterozygous mutant mice exhibit adult-onset DM1 phenotypes. With the additional mutation in Dmwd, the quadruple heterozygous mutant mice recapitulate many major manifestations in congenital DM1. Moreover, muscle stem cells in both models display reduced stemness, providing a unique model for screening small molecules for treatment of DM1. Our results suggest that the complex symptoms of DM1 result from the reduced dosage of multiple genes.

The demand for improved gasoline product quality has helped make molecular-level models become more preferred for the modern refinery. Building the molecular compositional model is an essential first step for this quantitative molecular management of gasoline streams. Gas chromatography equipped with flame ion detection (GC-FID) is commonly used in the gasoline detailed hydrocarbon analysis (DHA). The combination of GC-FID analysis and molecular-level modeling is thus very attractive. In the present study, we developed a gasoline compositional model based solely on GC-FID as input. To suppress the negative influence of peak coelution, we developed a statistics-based peak tuning algorithm to obtain individual compound resolution at higher carbon number range. Using the tuned result as input, the molecular-level gasoline compositional model was built by estimating the quantitative percentages of the species in a predefined molecular library (573 molecules). The molecular-level compositional model has good extensibility and can link to the molecule-based physical properties prediction model. The model has been verified via applications on various gasoline samples. The prediction of research octane number for large-scale gasoline samples was also revealed.

The beveled mesa structure of β-Ga2O3has attracted wide attention because it can significantly weaken the peak electric field and increase the breakdown voltage. In this study, β-Ga2O3beveled mesa has been modulated via inductively coupled plasma (ICP) etching with the etching precursors of BCl3and Ar. And the morphology of the sidewall has been investigated by properly adjusting the etching parameters, realizing different beveled angles owing to the different ratios of chemical etching and physical etching. The effect of ICP etching on the sidewall morphology of the β-Ga2O3beveled mesa was also studied. This study provides important guidance for the realization of higher-power devices based on β-Ga2O3.

The β-Ga2O3ultraviolet (UV) detectors work in the solar-blind (UV) band due to the ultra-wide bandgap of β-Ga2O3. In this paper, a solar-blind ultraviolet detector based on an ordered nanoporous β-Ga2O3(ONP-β-Ga2O3) film is proposed and implemented. The local enhancement effect of the ordered nanopores on light is simulated by finite-difference time-domain method, and the period and diameter of the nanopores are optimized. Graphene is transferred on the ONP-β-Ga2O3film and prepared as interdigital electrodes of the solar-blind ultraviolet detectors. The optimal detector has a photo-to-dark current ratio of about 4.64 × 103at a 5 V bias, a peak response of 2.43 A W−1at 254 nm, and a UV/visible rejection ratio of about 1081. We demonstrate that the ordered nanoporous structure can localize optical field effectively, which results in enhancement of light absorption as well as improvement of key detector parameters.

Recently, β‐Ga2O3and black phosphorus (BP) have attracted enormous attention as the solar‐blind ultraviolet (UV) and infrared (IR) photosensitive materials for next‐generation optoelectronic devices, respectively, due to their special bandgap and electrical characteristics. Many β‐Ga2O3‐based UV photodetectors and BP‐based IR photodetectors have been investigated separately, but there is no report on the heterojunction and photoelectric devices formed by these two excellent materials. Herein, metalorganic chemical vapor deposition (MOCVD) heteroepitaxial β‐Ga2O3and BP pn heterojunction for solar‐blind UV and IR dual‐band photodetector is proposed and demonstrated for the first time. The device demonstrates a remarkable photoresponse under UV and IR irradiations with a responsivity of 88.5 and 1.24 mA W−1, respectively, clear pn heterojunction characteristics, as well as an excellent photoswitch periodicity. Moreover, under different irradiation conditions, the photoelectric properties of β‐Ga2O3/BP pn heterojunction, including their photogeneration and photoresponse, are investigated in detail. These results signify that β‐Ga2O3/BP pn heterojunction may find potential applications in future UV/IR dual‐band detection systems. Metalorganic chemical vapor deposition heteroepitaxial β‐Ga2O3and black phosphorus pn heterojunction for solar‐blind ultraviolet and infrared dual‐band photodetector is proposed and demonstrated for the first time. The device demonstrates a remarkable photoresponse, clear pn heterojunction characteristics, as well as an excellent photoswitch periodicity. Moreover, the photoelectric properties of β‐Ga2O3/BP pn heterojunction are investigated in detail.

Surfaces designed to reduce the contact time of impacting droplets are potentially of great importance for fundamental science and technological applications, for example, anti-icing, self-cleaning and heating transfer applications. Previous studies have shown that the contact time can be reduced via introducing one or several crossing macroscale wires on superhydrophobic surfaces (SHSs). However, the impacts that strike far from the wires (off-center impacts) have contact times that are equal to those obtained on SHSs. Here we demonstrate that this problem can be largely solved by using macro anisotropic SHSs (macro-aniso-SHSs)—in which the wires are parallel and macroscaled. The droplet contact time depends on the spacing between the macrostripes and is remarkably reduced by 40–50% when the spacing is comparable to the droplet size. Obvious differences in the contact time are not observed for impacts that are centered on the stripe and in the groove. The impacts centered in the groove produce new hydrodynamics that are characterized by extended spreading, easy break up and bouncing in a flying-eagle configuration. The study discusses the underlying mechanisms of the impact processes. Moreover, the effect of parallel wires on the contact time is discussed by comparing the droplet impact data for grooved rice leaves and non-grooved cabbage leaves. The enhanced drop mobility associated with the macro-aniso-SHSs should be very useful in many industrial applications.