[Construction and Analysis of Machine Learning Based Transportation Carbon Emission Prediction Model].

Addressing the issue of carbon emissions in the transportation sector, this research constructed various predictive models using multiple machine learning algorithms based on panel data from 30 provinces in China from 2005 to 2019. The study aimed to identify the optimal machine learning algorithm and key factors influencing the carbon emissions of transportation, providing potent references for policymakers and decision-makers to reduce carbon emissions and promote the sustainable development of the transportation sector. Initially, drawing from the concept of the fixed effects model, we included the heterogeneity differences among provinces as an important factor. We further employed a combined method of Pearson's correlation coefficient and Spearman's rank correlation coefficient to screen 18 factors influencing transportation carbon emissions. We then made a preliminary selection of seven common machine learning algorithms and used the screened factors as explanatory variables for model training. The three algorithms with the best performance were further optimized and trained. Subsequently, we utilized the K-fold cross-validation method; plotted learning curves to test the performance of each predictive model; and used MSE, MAE, R2, and MAPE as evaluation indicators to determine the best predictive model. SHAP values were chosen to calculate the importance of each explanatory variable in the optimal predictive model. The results indicated that the multicollinearity among the seven factors of provincial differences, total consumption of social goods, urban green space area, freight turnover, number of private cars, transportation industry output, and permanent population was weak, and all passed the significance test. They could be used as explanatory variables in the prediction model of transportation carbon emissions. The prediction results of the Random Forest and XGBoost algorithms were both outstanding, with R2 values above 0.97 and errors below 10 %, showing no signs of overfitting or underfitting. Among them, the XGBoost algorithm performed the best, whereas the KNN algorithm performed poorly. The importance ranking of the explanatory variables was as follows:provincial differences > total consumption of social goods > number of private cars > permanent population > freight turnover > urban green space area > transportation industry output. A comprehensive analysis of relevance and importance showed that provincial differences were an indispensable variable in the prediction of transportation carbon emissions. In conclusion, this study provides a new approach to the governance of carbon emissions in the transportation industry, and the results can serve as a reference for policymakers and decision-makers. In future policy design and decision-making, the distinctive factors of each province should not be overlooked. Measures targeted at specific regions need to be formulated to promote the sustainable development of the transportation industry.

Discovery of Photoexcited 2-Chloro-3,5-Dinitrobenzoic Acid as a Chemical Deprenylase of i6A RNA.

RNA modifications play crucial roles in regulating gene expression and cellular homeostasis. Modulating RNA modifications, particularly by targeting the enzymes responsible for their catalysis, has emerged as a promising therapeutic strategy. However, limitations, such as the lack of identified modifying enzymes and compensatory mechanisms, hinder targeted interventions. Chemical approaches independent of enzymatic activity offer an alternative strategy for RNA modification modulation. Here, we present the identification of 2-chloro-3,5-dinitrobenzoic acid as a highly effective photochemical deprenylase of i6A RNA. This method demonstrates exceptional selectivity towards i6A, converting its substituent into a "N-doped" ozonide, which upon hydrolysis releases natural adenine. We believe that this chemical approach will pave the way for a better understanding of RNA modification biology and the development of novel therapeutic modalities.

Longitudinal manipulation of local nonseparability in vector beams.

The inherent nonseparability of vector beams presents a unique opportunity to explore novel optical functionalities, expanding new degrees of freedom for optical information processing. In this Letter, we introduce a novel, to the best of our knowledge, method for tailoring the local nonseparability along the propagation axis of vector beams. Employing higher-order Bessel vector beams, the longitudinal control over the local nonseparability is achieved through targeted amplitude modulation of constituent orthogonal polarization components within the main ring region. Experimental demonstrations of diverse longitudinal nonseparability profiles corroborate the efficacy and versatility of our approach, opening avenues for further exploration of the nonseparability manipulation in vector beams.

Upregulated lncRNA PRNT promotes progression and oxaliplatin resistance of colorectal cancer cells by regulating HIPK2 transcription.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and a significant cause of cancer-related mortality globally. Resistance to chemotherapy, especially during CRC treatment, leads to reduced effectiveness of drugs and poor patient outcomes. Long noncoding RNAs (lncRNAs) have been implicated in various pathophysiological processes of tumor cells, including chemotherapy resistance, yet the roles of many lncRNAs in CRC remain unclear. AIM: To identify and analyze the lncRNAs involved in oxaliplatin resistance in CRC and to understand the underlying molecular mechanisms influencing this resistance. METHODS: Gene Expression Omnibus datasets GSE42387 and GSE30011 were reanalyzed to identify lncRNAs and mRNAs associated with oxaliplatin resistance. Various bioinformatics tools were employed to elucidate molecular mechanisms. The expression levels of lncRNAs and mRNAs were assessed via quantitative reverse transcription-polymerase chain reaction. Functional assays, including MTT, wound healing, and Transwell, were conducted to investigate the functional implications of lncRNA alterations. Interactions between lncRNAs and transcription factors were examined using RIP and luciferase reporter assays, while Western blotting was used to confirm downstream pathways. Additionally, a xenograft mouse model was utilized to study the in vivo effects of lncRNAs on chemotherapy resistance. RESULTS: LncRNA prion protein testis specific (PRNT) was found to be upregulated in oxaliplatin-resistant CRC cell lines and negatively correlated with homeodomain interacting protein kinase 2 (HIPK2) expression. PRNT was demonstrated to sponge transcription factor zinc finger protein 184 (ZNF184), which in turn could regulate HIPK2 expression. Altered expression of PRNT influenced CRC cell sensitivity to oxaliplatin, with overexpression leading to decreased sensitivity and decreased expression reducing resistance. Both RIP and luciferase reporter assays indicated that ZNF184 and HIPK2 are targets of PRNT. The PRNT/ZNF184/HIPK2 axis was implicated in promoting CRC progression and oxaliplatin resistance both in vitro and in vivo. CONCLUSION: The study concludes that PRNT is upregulated in oxaliplatin-resistant CRC cells and modulates the expression of HIPK2 by sponging ZNF184. This regulatory mechanism enhances CRC progression and resistance to oxaliplatin, positioning PRNT as a promising therapeutic target for CRC patients undergoing oxaliplatin-based chemotherapy.

Selective Methylation of Nucleosides via an In Situ Generated Methyl Oxonium.

A very mild and efficient procedure has been developed for the preparation of N-methylated uridine, pseudouridine, guanosine and inosine derivatives. This process was compatible with free hydroxyls within the ribose and did not require precautions on the protection or deprotection of other functionalities. The key to this extremely mild methylation without protection relied on the in situ generated methyl oxonium from the Wittig reagent and methanol. A putative mechanism for the selective methylation was also proposed.

Tailoring nonuniform local orbital angular momentum density.

As is well known, a light beam with a helical phase carries an optical orbital angular momentum (OAM), which can cause the orbital motion of trapped microparticles around the beam axis. Usually, the speed of the orbital motion is uniform along the azimuthal direction and depends on the amount of OAM and the light intensity. Here, we present the reverse customized method to tailor the nonuniform local OAM density along the azimuthal direction of the focal field, which has a hybrid polarization distribution and maintains a doughnut-shaped intensity profile. Theoretical analysis and experimental results about the orbital motion of the trapped polystyrene sphere show that the nonuniform local OAM density can be tailored by manipulating the polarization states of the focal field. Our results provide an ingenious way to control the local tangential optical force and the speed of the orbital motion of particles driven by the local OAM density and will promote exciting possibilities for exploring ways to control the mechanical dynamics of microparticles in optical trapping and microfluidics.

Could the presence and proportion of three/multiple pronuclei (3PN/MPN) zygotes indicate the cytoplasmic maturation state of oocyte cohort in conventional IVF patients?

Although abnormally fertilized zygotes with three or multiple pronuclei (3 PN/MPN) are commonly believed to be associated with improper maturation of the oocyte cytoplasm in conventional IVF cycles, no studies investigated the association between the proportion of MPN zygotes and the maturation state of the oocyte cohort. We compared the cytoplasmic maturity of oocytes from conventional IVF cycles with different proportions of 3 PN/MPN zygotes. A total of 1428 conventional IVF patients with ≥6 oocytes retrieved and fresh embryos transferred were divided into 4 groups according to the proportions of 3 PN/MPN zygotes. The pregnancy outcomes and the proportion of nuclear immature oocytes were analyzed to suggest the cytoplasmic maturation state of the oocyte cohort. Our results showed that the group with a low proportion of 3 PN/MPN zygotes had a higher clinical pregnancy rate (CPR) than those without 3 PN/MPN zygotes (P < 0.05). However, the live birth rate (LBR) was not significantly different between the two groups. The implantation rate (IR), CPR, and LBR did not differ between the low-proportion and high-proportion 3 PN/MPN groups. The proportion of nuclear immature oocytes on day 1 was highest in the group without 3 PN/MPN zygotes (23.8 %) and gradually decreased with an increased proportion of 3 PN/MPN zygotes (P < 0.001). Therefore, the presence of 3 PN/MPN zygotes after conventional IVF may indicate a more mature cytoplasmic state of the oocyte cohort, and the increased proportion of 3 PN/MPN zygotes is associated with an increased maturation state of the whole oocyte cohort. The occurrence and proportion of 3 PN/MPN zygotes may serve as an indicator for the cytoplasmic maturity of the oocyte cohort and help clinicians evaluate the efficiency of ovarian stimulation and optimize the stimulation protocols in subsequent cycles.

Grafting seedling rootstock strengthens tolerance to drought stress in polyploid mulberry (Morus alba L.).

The economically adaptable mulberry (Morus alba L.) has a long history of grafting in China, yet the physiological mechanisms and advantages in drought tolerance remain unexplored. In our study, we investigated the responses of self-rooted 2X (diploid), 3X (triploid), and 4X (tetraploid) plants, as well as polyploid plants grafted onto diploid seedling rootstocks (2X/2X, 3X/2X, and 4X/2X) under drought stress. We found that self-rooted diploid plants exhibited the most severe phenotypic damage, lowest water retention, photosynthetic capacity, and the least effective osmotic stress adjustment compared to tetraploid and triploid plants. However, grafted diploid and triploid plants showed effective mitigation of drought-induced damage, with higher relative water content and improved soil water retention. Grafted plants also improved the photosystem response to drought stress through elevated photosynthetic potential, closed stomatal aperture, and faster recovery of chlorophyll biosynthesis in the leaves. Additionally, grafted plants altered osmotic protective compound levels, including starch, soluble sugar, and proline content, thereby enhancing drought resistance. Absolute quantification PCR indicated that the expression levels of proline synthesis-related genes in grafted plants were not influenced after drought stress, whereas they were significantly increased in self-rooted plants. Consequently, our findings support that self-rooted triploid and tetraploid mulberries exhibited superior drought resistance compared to diploid plants. Moreover, grafting onto seedling rootstocks enhanced tolerance against drought stress in diploid and triploid mulberry, but not in tetraploid. Our study provides valuable insights for a comprehensive analysis of physiological effects in response to drought stress between stem-roots and seedling rootstocks.

Identification of Scolopendra Dispensing Granules by Allele-specific PCR / 中国实验方剂学杂志

ObjectiveTo establish an allele-specific polymerase chain reaction （PCR） method for identifying Scolopendra dispensing granules， so as to ensure the quality and therapeutic effects of Scolopendra and its preparations. MethodThe primer interval suitable for the PCR was selected based on the cytochrome c oxidase subunit 3（COX-3） gene sequence of Scolopendra， and the single nucleotide polymorphism （SNP） loci of Scolopendra and its adulterants were mined from the interval for the design of specific primers. The samples of Scolopendra and its adulterants were collected. The PCR system was established and optimized regarding the annealing temperature， cycles， Taq enzymes， DNA template amount， PCR instruments， and primer concentrations， and the specificity and applicability of this method were evaluated. ResultThe PCR system was composed of 12.5 μL 2×M5 PCR Mix， 0.4 μL forward primer （10 μmol·L-1）， 0.4 μL reverse primer （10 μmol·L-1）， 2.5 μL DNA template， and 9.2 μL sterile double distilled water. PCR parameters： Pre-denaturation at 94 ℃ for 3 min， 30 cycles （94 ℃ for 20 s， 62 ℃ for 20 s， 72 ℃ for 45 s）， and extension at 72 ℃ for 5 min. After PCR amplification with the system and parameters above， the electrophoresis revealed a bright band at about 135 bp for Scolopendra and no band for the adulterants. ConclusionThe established allele-specific PCR method can accurately identify the medicinal materials， decoction pieces， and standard decoction freeze-dried powder of Scolopendra， as well as the intermediates and final products of Scolopendra dispensing granules， which is of great significance for ensuring the quality and clinical efficacy of Scolopendra and its preparations.

A Rapid PCR-RFLP Method for Assessing Heterozygosity of Murraya paniculata Germplasm / 中国实验方剂学杂志

ObjectiveTo establish a rapid method for evaluating the heterozygosity of Murraya paniculata germplasm materials and provide as a foundation for developing germplasm breeding and innovation measures for M. paniculata. MethodSingle nucleotide polymorphisms （SNPs） were screened from the genome resequencing data of 65 plants of M. paniculata. A self-written script was used to transform 20 SNPs into restriction fragment length polymorphism （RFLP） markers. Polymerase chain reaction-restriction fragment length polymorphism （PCR-RFLP） was employed to detect the 20 RFLP markers in 12 M. paniculata germplasm accessions， and the heterozygosity of M. paniculata germplasm accessions was calculated based on the number of enzyme-cutting bands at the 20 RFLP marker sites. Plink was used to calculate the whole genome heterozygosity of 12 M. paniculata germplasm accessions， and the results obtained with different methods were compared. ResultThere was no significant difference in the heterozygosity calculated by the PCR-RFLP method and the genome resequencing method. The PCR-RFLP and genome resequencing methods identified 8 and 9 germplasm accessions， respectively， with a heterozygosity level less than 30%. Seven germplasm accessions with heterozygosity less than 30.00% were calculated by both methods. ConclusionThe PCR-RFLP method established in this study for evaluating the heterozygosity of M. paniculata germplasm demonstrates the precision of 87.5% and the accuracy of 77.8%. This method serves as a reference for developing heterozygosity evaluation methods in other medicinal plant germplasm resources.

Enzyme-linked Immunosorbent Assay in Quality Control of Chinese Medicines： A Review / 中国实验方剂学杂志

In the quality control of Chinese medicine， the detection of active components and toxic and harmful components are two important links. Although conventional methods such as high performance liquid chromatography and liquid chromatography-mass spectrometry can accurately quantify the above substances， they have shortcomings such as complicated operation， high costs， inability of detection at any time， difficult detection of insoluble and macromolecular substances. Enzyme-linked immunosorbent assay （ELISA） can adsorb antigens or antibodies on the surface of solid carriers and realize qualitative or quantitative analysis of targets by using the specific reactions of antigens and antibodies. This method is praised for the simple operation， high sensitivity， strong specificity， simple requirements for experimental equipment， a wide application range， and low costs. In recent years， ELISA has been widely used in the quality control of Chinese medicine， especially in the content determination of mycotoxins represented by aflatoxin and the qualitative and quantitative analysis of active components. ELISA plays an increasingly important role with its unique advantages， providing new methods and ideas for the rapid quality examination of large quantities of Chinese medicines. This paper reviews the research progress in ELISA for the quality control of Chinese medicine in recent years and prospects its technical development and application prospects， aiming to provide reference and research ideas for further using this method to ensure the quality， safety， and controllability of Chinese medicine.

Single-shot measurement of the Jones matrix for anisotropic media using four-channel digital polarization holography.

Dynamic measurement of the Jones matrix is crucial in investigating polarization light fields, which have wide applications in biophysics, chemistry, and mineralogy. However, acquiring the four elements of the Jones matrix instantly is difficult, hindering the characterization of random media and transient processes. In this study, we propose a single-shot measurement method of the Jones matrix for anisotropic media called "four-channel digital polarization holography" (FC-DPH). The FC-DPH system is created by a slightly off-axis superposition of reference light waves, which are modulated by a spatial light modulator (SLM), and signal light waves that pass through a Ronchi grating. The SLM enables flexible adjustment of the spatial carrier frequency, which can be adapted to different anisotropic media. The four elements of the Jones matrix can be obtained from the interferogram through the inverse Fourier transform. Optical experiments on anisotropic objects validate the feasibility and accuracy of the proposed method.

Double-Shock Compression Pathways from Diamond to BC8 Carbon.

Carbon is one of the most important elements for both industrial applications and fundamental research, including life, physics, chemistry, materials, and even planetary science. Although theoretical predictions on the transition from diamond to the BC8 (Ia3[over ¯]) carbon were made more than thirty years ago, after tremendous experimental efforts, direct evidence for the existence of BC8 carbon is still lacking. In this study, a machine learning potential was developed for high-pressure carbon fitted from first-principles calculations, which exhibited great capabilities in modeling the melting and Hugoniot line. Using the molecular dynamics based on this machine learning potential, we designed a thermodynamic pathway that is achievable for the double shock compression experiment to obtain the elusive BC8 carbon. Diamond was compressed up to 584 GPa after the first shock at 20.5 km/s. Subsequently, in the second shock compression at 24.8 or 25.0 km/s, diamond was compressed to a supercooled liquid and then solidified to BC8 in around 1 ns. Furthermore, the critical nucleus size and nucleation rate of BC8 were calculated, which are crucial for nano-second x-ray diffraction measurements to observe BC8 carbon during shock compressions. The key to obtaining BC8 carbon lies in the formation of liquid at a sufficient supercooling. Our work provides a feasible pathway by which the long-sought BC8 phase of carbon can be reached in experiments.

Groundwater vulnerability assessment of nitrate pollution in the Ankang Basin: using an optimized DRASTIC-LY method.

This study retains the basic structure of DRASTIC model and obtains more specific evaluation results by adding land-use type and groundwater resource yield parameters, modifying the rating scale and weight of nine parameters. Comparison of the modified DRASTIC-LY vulnerability map with the map of the original DRASTIC-LY method revealed differences in 40.49% of the study area. The risk map shows that the very high vulnerability area decreased from 2.79 to 1.67%, while the high vulnerability area increased from 18.70 to 28.86%. Areas with low vulnerability increased by 10.15%, while areas with medium vulnerability decreased by 15.01%. The areas with very high groundwater vulnerability are mainly distributed in the Hanbin area on the north bank of the Han River, the areas with high are mainly concentrated on both sides of the Fujia River, while the areas with low are distributed in most areas in the west of the basin. The Pearson's correlation factor was 0.0583 in the original DRASTIC model, 0.1113 in the DRASTIC-LY method and 0.8291 in the modified DRASTIC-LY model, which indicated that the revised DRASTIC-LY model was more appropriate than the original model. The results can help the government with the protection of water resources.

Spatio-temporal structuring control of a vectorial focal field.

Focal field modulation has attracted a lot of interest due to its potential in many applications such as optical tweezers or laser processing, and it has recently been facilitated by spatial light modulators (SLMs) owing to their dynamic modulation abilities. However, capabilities for manipulating focal fields are limited by the space-bandwidth product of SLMs. This difficulty can be alleviated by taking advantage of the high-speed modulation ability of digital micromirror devices (DMDs), i.e., trading time for space to achieve fine focus shaping. In this paper, we propose a new, to the best of our knowledge, technique for achieving four-dimensional focal field modulation, which allows for independent manipulation of the focal field's parameters (including amplitude, phase, and polarization) in both the space and time domains. This technique combines a DMD and a vector field synthesis system based on a 4-f system. The high-speed modulation ability of DMDs enables versatile focus patterns to be fast switchable during the exposure time of the detector, forming multiple patterns in a single recording frame. By generating different kinds of focal spots and lines at different moments during the exposure time of the detector, we can finally get complete multifocal spots and lines. Our proposed method is effective at improving the flexibility and speed of the focal field modulation, which is beneficial to applications.

High expression of autophagy-related gene EIF4EBP1 could promote tamoxifen resistance and predict poor prognosis in breast cancer.

BACKGROUND: Breast cancer (BC) remains a public health problem. Tamoxifen (TAM) resistance has caused great difficulties for treatment of BC patients. Eukaryotic translation initiation factor 4E binding protein 1 (EIF4EBP1) plays critical roles in the tumorigenesis and progression of BC. However, the expression and mechanism of EIF4EBP1 in determining the efficacy of TAM therapy in BC patients are still unclear. AIM: To investigate the expression and functions of EIF4EBP1 in determining the efficacy of TAM therapy in BC patients. METHODS: High-throughput sequencing data of breast tumors were downloaded from the Gene Expression Omnibus database. Differential gene expression analysis identified EIF4EBP1 to be significantly upregulated in cancer tissues. Its prognostic value was analyzed. The biological function and related pathways of EIF4EBP1 was analyzed. Subsequently, the expression of EIF4EBP1 was determined by real-time reverse transcription polymerase chain reaction and western blotting. Cell Counting Kit-8 assays, colony formation assay and wound healing assay were used to understand the phenotypes of function of EIF4EBP1. RESULTS: EIF4EBP1 was upregulated in the TAM-resistant cells, and EIF4EBP1 was related to the prognosis of BC patients. Gene Set Enrichment Analysis showed that EIF4EBP1 might be involved in Hedgehog signaling pathways. Decreasing the expression of EIF4EBP1 could reverse TAM resistance, whereas overexpression of EIF4EBP1 promoted TAM resistance. CONCLUSION: This study indicated that EIF4EBP1 was overexpressed in the BC and TAM-resistant cell line, which increased cell proliferation, invasion, migration and TAM resistance in BC cells.

MAGUS: machine learning and graph theory assisted universal structure searcher.

Crystal structure predictions based on first-principles calculations have gained great success in materials science and solid state physics. However, the remaining challenges still limit their applications in systems with a large number of atoms, especially the complexity of conformational space and the cost of local optimizations for big systems. Here, we introduce a crystal structure prediction method, MAGUS, based on the evolutionary algorithm, which addresses the above challenges with machine learning and graph theory. Techniques used in the program are summarized in detail and benchmark tests are provided. With intensive tests, we demonstrate that on-the-fly machine-learning potentials can be used to significantly reduce the number of expensive first-principles calculations, and the crystal decomposition based on graph theory can efficiently decrease the required configurations in order to find the target structures. We also summarized the representative applications of this method on several research topics, including unexpected compounds in the interior of planets and their exotic states at high pressure and high temperature (superionic, plastic, partially diffusive state, etc.); new functional materials (superhard, high-energy-density, superconducting, photoelectric materials), etc. These successful applications demonstrated that MAGUS code can help to accelerate the discovery of interesting materials and phenomena, as well as the significant value of crystal structure predictions in general.

Nurses' clinical competency and its correlates: before and during the COVID-19 outbreak.

BACKGROUND: Clinical competency is the ability to integrate knowledge, skills, attitudes and values into a clinical situation and it is very important in nursing education, clinical settings, nursing management, and crises. This study aimed to investigate nurses' professional competence and its correlates before and during the COVID-19 pandemic. METHODS: We conducted this cross-sectional study before and during the COVID-19 outbreak and recruited all nurses working in hospitals affiliated to Rafsanjan University of Medical Sciences, southern Iran, so we included 260 and 246 nurses in the study before and during the COVID-19 epidemic, respectively. Competency Inventory for Registered Nurses (CIRN) was used to collect data. After inputting the data into SPSS24, we analysed them using descriptive statistics, chi-square and multivariate logistic tests. A significant level of 0.05 was considered. RESULTS: The mean clinical competency scores of nurses were 156.97 ± 31.40 and 161.97 ± 31.36 before and during the COVID-19 epidemic, respectively. The total clinical competency score before the COVID-19 epidemic was not significantly different from that during the COVID-19 epidemic. Interpersonal relationships (p = 0.03) and desire for research/critical thinking (p = 0.01) were significantly lower before the COVID-19 outbreak than during the COVID-19 outbreak. Only shift type had an association with clinical competency before the COVID-19 outbreak, while work experience had an association with clinical competency during the COVID-19 epidemic. CONCLUSION: The clinical competency among nurses was moderate before and during the COVID-19 epidemic. Paying attention to the clinical competence of nurses can improve the care conditions of patients, and nursing managers should improve the clinical competence of nurses in different situations and crises. Therefore, we suggest further studies identifying factors improving the professional competency among nurses.

Infrared Image Caption Based on Object-Oriented Attention.

With the ongoing development of image technology, the deployment of various intelligent applications on embedded devices has attracted increased attention in the industry. One such application is automatic image captioning for infrared images, which involves converting images into text. This practical task is widely used in night security, as well as for understanding night scenes and other scenarios. However, due to the differences in image features and the complexity of semantic information, generating captions for infrared images remains a challenging task. From the perspective of deployment and application, to improve the correlation between descriptions and objects, we introduced the YOLOv6 and LSTM as encoder-decoder structure and proposed infrared image caption based on object-oriented attention. Firstly, to improve the domain adaptability of the detector, we optimized the pseudo-label learning process. Secondly, we proposed the object-oriented attention method to address the alignment problem between complex semantic information and embedded words. This method helps select the most crucial features of the object region and guides the caption model in generating words that are more relevant to the object. Our methods have shown good performance on the infrared image and can produce words explicitly associated with the object regions located by the detector. The robustness and effectiveness of the proposed methods were demonstrated through evaluation on various datasets, along with other state-of-the-art methods. Our approach achieved BLUE-4 scores of 31.6 and 41.2 on KAIST and Infrared City and Town datasets, respectively. Our approach provides a feasible solution for the deployment of embedded devices in industrial applications.

Characterization of Orbital Angular Momentum Quantum States Empowered by Metasurfaces.

Twisted photons can in principle carry a discrete unbounded amount of orbital angular momentum (OAM), which are of great significance for quantum communication and fundamental tests of quantum theory. However, the methods for characterization of the OAM quantum states present a fundamental limit for miniaturization. Metasurfaces can exploit new degrees of freedom to manipulate optical fields beyond the capabilities of bulk optics, opening a broad range of novel and superior applications in quantum photonics. Here we present a scheme to reconstruct the density matrix of the OAM quantum states of single photons with all-dielectric metasurfaces composed of birefringent meta-atoms. We have also measured the Schmidt number of the OAM entanglement by the multiplexing of multiple degrees of freedom. Our work represents a step toward the practical application of quantum metadevices for the measurement of OAM quantum states in free-space quantum imaging and communications.