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Printed circuit boards present several challenges to the detection of defects, including targets of insufficient size and distribution, a high level of background noise, and a variety of complex types. These factors contribute to the difficulties encountered by PCB defect detection networks in accurately identifying defects. This paper proposes a less-parametric model, YOLO-RRL, based on the improved YOLOv8 architecture. The YOLO-RRL model incorporates four key improvement modules: The following modules have been incorporated into the proposed model: Robust Feature Downsampling (RFD), Reparameterised Generalised FPN (RepGFPN), Dynamic Upsampler (DySample), and Lightweight Asymmetric Detection Head (LADH-Head). The results of multiple performance metrics evaluation demonstrate that YOLO-RRL enhances the mean accuracy (mAP) by 2.2 percentage points to 95.2%, increases the frame rate (FPS) by 12%, and significantly reduces the number of parameters and the computational complexity, thereby achieving a balance between performance and efficiency. Two datasets, NEU-DET and APSPC, were employed to evaluate the performance of YOLO-RRL. The results indicate that YOLO-RRL exhibits good adaptability. In comparison to existing mainstream inspection models, YOLO-RRL is also more advanced. The YOLO-RRL model is capable of significantly improving production quality and reducing production costs in practical applications while also extending the scope of the inspection system to a wide range of industrial applications. [ABSTRACT FROM AUTHOR]

Background: Attribution models have been examined in Western countries. However, little is known about the applicability of the attitude–emotion–behavior model within Chinese culture. This study aimed to examine the association between familiarity, perceived dangerousness, fear, and social distance towards persons with mental illness (PMI) in the Chinese context. Methods: An online cross-sectional survey was conducted from October to November 2022 in mainland China. A total of 1493 college students completed a questionnaire evaluating familiarity, perception of dangerousness, fear, and social distance regarding PMI. Path analysis was employed to validate the model proposed in this study. Results: Participants expressed moderate to high levels of stigma towards PMI. Familiarity was negatively associated with social distance (p < 0.01). Participants who perceived PMI as dangerous were more prone to exhibit a reaction of fear (p < 0.001), consequently leading to social distance (p < 0.01). However, the mediating effect of perceived dangerousness and fear on the relationship between familiarity and social distance was not significant (p > 0.05). Conclusions: The results of this study provide support for Corrigan's attributional model of stigma in the Chinese context. Contact-based interventions for stigma reduction should emphasize multiple elements of contact, including the quality of contact, rather than familiarity. [ABSTRACT FROM AUTHOR]

Non-contact temperature sensors utilising the fluorescence intensity ratio and the unique up-conversion (UC) luminescence of rare-earth ions have numerous benefits; however, their operational temperature range has remained limited. In this study, NaLuF4:Yb3+/Ho3+ samples were prepared by the hydrothermal method. The samples exhibited exceptional UC luminescence properties at low temperatures. The intensity of the green emission (with peak wavelengths of 540 and 546 nm) gradually decreased with increasing temperature, and the green emissions showed a unique change at low temperatures. In addition, we studied the dependence of the UC luminescence intensity on the excitation power and the variation in the decay lifetime with temperature. The experiments revealed excellent luminous performance and significantly enhanced sensitivity at low temperatures; the maximum absolute sensitivity Sa and relative sensitivity Sr of the 540 and 546 nm thermally coupled energy levels were 1.02% and 0.55% K−1, respectively. The potential temperature sensing properties of Yb3+/Ho3+-co-doped NaLuF4 makes it suitable for temperature sensing applications at temperatures as low as 30 K. This study offers a novel approach for the advancement of temperature sensing technology at low temperatures. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is growing into a major public health crisis worldwide. The reducing alternatives to conventional agents starve for novel antimicrobial agents. Due to their unique magnetic properties and excellent biocompatibility, iron oxide nanoparticles (IONPs) are the most preferable nanomaterials in biomedicine, including antibacterial therapy, primarily through reactive oxygen species (ROS) production. IONP characteristics, including their size, shape, surface charge, and superparamagnetism, influence their biodistribution and antibacterial activity. External magnetic fields, foreign metal doping, and surface, size, and shape modification improve the antibacterial effect of IONPs. Despite a few disadvantages, IONPs are expected to be promising antibacterial agents of a new generation. [ABSTRACT FROM AUTHOR]

Simple Summary: The flea beetle Asiophrida xanthospilota (Baly, 1881) is a serious forest pest specifically damaging the common smoketree Cotinus coggygria. To understand how this beetle sees the world, we used scanning electron microscopy, transmission electron microscopy, micro-computed tomography, and three-dimensional reconstruction to investigate the external morphology and internal ultrastructure of the compound eye. The examination showed that of Asi. xanthospilota has apposition eye like other leaf beetles, consisting of a subplano-convex cornea, an acone of four cone cells, eight retinular cells along with an open rhabdom, as well as two primary pigment cells and about 23 secondary pigment cells. Interestingly, retinular cell 8 does not contribute to the rhabdom. We also investigated the spectral sensitivity by electroretinogram tests and phototropism experiments. Electroretinogram tests showed that Asi. xanthospilota exhibits the strongest sensitivity to blue and green lights but the weakest to red light. Phototropism experiments also revealed that this beetle has the strongest reaction to blue light. In this study, the morphology and ultrastructure of the compound eye of Asi. xanthospilota were examined by using scanning electron microscopy (SEM), transmission electron microscopy (TEM), micro-computed tomography (μCT), and 3D reconstruction. Spectral sensitivity was investigated by electroretinogram (ERG) tests and phototropism experiments. The compound eye of Asi. xanthospilota is of the apposition type, consisting of 611.00 ± 17.53 ommatidia in males and 634.8 0 ± 24.73 ommatidia in females. Each ommatidium is composed of a subplano-convex cornea, an acone consisting of four cone cells, eight retinular cells along with the rhabdom, two primary pigment cells, and about 23 secondary pigment cells. The open type of rhabdom in Asi. xanthospilota consists of six peripheral rhabdomeres contributed by the six peripheral retinular cells (R1~R6) and two distally attached rhabdomeric segments generated solely by R7, while R8 do not contribute to the rhabdom. The orientation of microvilli indicates that Asi. xanthospilota is unlikely to be a polarization-sensitive species. ERG testing showed that both males and females reacted to stimuli from red, yellow, green, blue, and ultraviolet light. Both males and females exhibited strong responses to blue and green light but weak responses to red light. The phototropism experiments showed that both males and females exhibited positive phototaxis to all five lights, with blue light significantly stronger than the others. [ABSTRACT FROM AUTHOR]

Progress in numerical models and improved computational capabilities have significantly advanced our comprehension of how aerosol particles impact thunderstorm clouds. Yet, much of this research has focused on employing bulk microphysics models to explain the impacts of aerosol particles acting as cloud condensation nuclei (CCN) on electrical activities in thunderstorm clouds. The bulk thunderstorm models use mean sizes of particles and terminal-fall velocities. This causes calculation deviation in the electrification simulation, which in turn leads to deviations in the simulation of lightning processes. Developing this further, we established a three-dimensional high-resolution cloud–aerosol bin thunderstorm model with electrification and lightning to provide more accurate microphysics and dynamic fields for studying electrical activities. For evaluating the impacts of aerosol particles, specifically CCN, on the properties of continental thunderclouds, aerosols from both clean and polluted continental environments were selected. Cloud simulations indicate that droplets develop a narrower spectrum in polluted continental conditions, and weakened ice crystal growth increases the number of small ice crystals compared to clean conditions. Smaller droplets and ice crystals result in less effective riming and decreased graupel concentration and mass. Consequently, a significant decrease in large ice particles leads to a weakened process of charge separation under conditions of pollution. As a direct result, there is about a 43% reduction in lightning frequency and a delay of approximately 5 min in the lightning process under polluted conditions. [ABSTRACT FROM AUTHOR]

The traditional detection methods of steel surface defects have some problems, such as a lack of feature extraction ability, sluggish detection speed, and subpar detection performance. In this paper, a YOLOv8-based DDI-YOLO model is suggested for effective steel surface defect detection. First, on the Backbone network, the extended residual module (DWR) is fused with the C2f module to obtain C2f_DWR, and the two-step approach is used to carry out the effective extraction of multiscale contextual information, and then fusing feature maps formed from the multiscale receptive fields to enhance the capacity for feature extraction. Also based on the above, an extended heavy parameter module (DRB) is added to the structure of C2f_DWR to make up for the lack of C2f's ability to capture small-scale pattern defects between training to enhance the training fluency of the model. Finally, the Inner-IoU loss function is employed to enhance the regression accuracy and training speed of the model. The experimental results show that the detection of DDI-YOLO on the NEU-DET dataset improves the mAP by 2.4%, the accuracy by 3.3%, and the FPS by 59 frames/s compared with the original YOLOv8n.Therefore, this paper's proposed model has a superior mAP, accuracy, and FPS in identifying surface defects in steel. [ABSTRACT FROM AUTHOR]

The PIESAT-01 constellation is the world's first multi-baseline distributed synthetic aperture radar (SAR) constellation with a "Cartwheel" formation. The "Cartwheel" formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the "Cartwheel" configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China's 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data. [ABSTRACT FROM AUTHOR]

Electromagnetic interference poses a significant challenge to the reliability and performance of electronic equipment, particularly in the aerospace and aviation sectors where the demand for high-performance electromagnetic shielding materials is paramount. This study introduces an innovative solution: a lightweight nickel-plated carbon fiber composite chassis, designed to meet these stringent requirements. Through comparative analysis, we prove that this composite chassis is not only comparable to traditional metal chassis in terms of time-domain shielding effect, but also close to traditional metal chassis in terms of heat dissipation capability. Notably, it achieves a substantial weight reduction of 71.43% to 76.25% compared to its metal counterparts, addressing the critical need for lighter materials in aerospace applications. The superior heat dissipation feature of the nickel-plated carbon fiber composite, quantitatively superior to conventional materials, indicates its potential to enhance the operational efficiency and safety of aerospace electronics. This research underscores the viability of nickel-plated carbon fiber composites as a groundbreaking material for electromagnetic shielding, promising significant advancements in aerospace and beyond. [ABSTRACT FROM AUTHOR]

Bacterial diversity and its distribution characteristics in sediments are critical to understanding and revealing biogeochemical cycles in sediments. However, little is known about the relationship between biogeochemistry processes and vertical spatial distribution of bacterial communities in sandy sediments. In this study, we used fluorescence quantitative PCR, high-throughput sequencing technology and statistical analysis to explore the vertical distribution pattern of bacterial community diversity and its influencing factors in sandy sediments of the Yangtze River Basin. The aim is to enrich the understanding of the ecological characteristics and functions of bacteria in river ecosystems. The results showed that both sediment bacterial abundance and diversity showed a gradual decrease from surface to bottom in the vertical distribution. The main environmental factors that influenced the bacterial distribution pattern were pore water dissolved oxygen (DO), total nitrogen (TN) concentration and sediment nitrogen (N) content. The dominant bacterial species, Massilia and Flavobacterium, are suitable for growth and reproduction in high oxygen and nutrient-richer environments, while Limnobacter prefers low oxygen or anaerobic conditions. The vertical distribution pattern of bacteria and its influencing factors in river sandy sediment found in this study differ from the results in mud sediment, which may be related to the larger granular gap between sandy sediment and the lower content of organic matter. The findings of this study further our understanding of the distribution patterns and ecological preferences of microbial communities in river sediments, providing insights into how these communities may adapt to varying environmental conditions. [ABSTRACT FROM AUTHOR]

Photomechanical molecular crystals, actuated by solid-state photochemical reactions, manifest a spectrum of mechanical motions upon light exposure, underscoring their prospective integration into the next generation of intelligent materials and devices. Utilizing the solid-state photodimerization of naphthyl acrylic acid as a paradigm, this study delved into the interplay between crystal morphology and reaction dynamics on the photomechanical responses of molecular crystals. Distinct crystal forms—bulk, microrods, and microplates—were cultivated through tailored crystallization conditions. While bulk crystals of naphthyl acrylic acid (NA) underwent shattering and splintering upon UV light exposure, the microplate counterparts displayed unique cracking patterns with fissures yet retained their overall structural integrity. In contrast, NA microrods underwent pronounced bending under identical irradiation conditions. These phenomena are attributed to the efficient lattice reconfiguration stemming from the [2 + 2] cycloaddition photochemical reaction within the crystals. An intermediate fluorescence enhancement was observed across all crystal types upon light exposure. Collectively, our results underscore the pivotal role of crystal shape in dictating photomechanical behavior, thereby heralding novel strategies for developing advanced photomechanical materials. [ABSTRACT FROM AUTHOR]

In this study, we investigate micrometer-sized NaYF4 crystals double-doped with Yb3+/Er3+ lanthanide ions, designed for temperature-sensing applications. In contrast to previous studies, which focused predominantly on the high-temperature regime, our investigation spans a comprehensive range of both high and ultralow temperatures. We explore the relationship between temperature and the upconversion luminescence (UCL) spectra in both frequency and time domains. Our findings highlight the strong dependence of these spectral characteristics of lanthanide-doped NaYF4 crystals on temperature. Furthermore, we introduce a dual-mode luminescence temperature measurement technique, leveraging the upconversion emission intensity ratio for both green and red emissions. This study also examines the correlation between temperature sensing, energy level disparities, and thermal coupling in Er3+ ions across various temperature scales. Our research contributes to advancing the understanding and application of lanthanide-doped materials, setting a foundation for future innovations in temperature sensing across diverse fields. [ABSTRACT FROM AUTHOR]

Obtaining accurate and real-time spatial distribution information regarding crops is critical for enabling effective smart agricultural management. In this study, innovative decision fusion strategies, including Enhanced Overall Accuracy Index (E-OAI) voting and the Overall Accuracy Index-based Majority Voting (OAI-MV), were introduced to optimize the use of diverse remote sensing data and various classifiers, thereby improving the accuracy of crop/vegetation identification. These strategies were utilized to integrate crop/vegetation classification outcomes from distinct feature sets (including Gaofen-6 reflectance, Sentinel-2 time series of vegetation indices, Sentinel-2 time series of biophysical variables, Sentinel-1 time series of backscatter coefficients, and their combinations) using distinct classifiers (Random Forests (RFs), Support Vector Machines (SVMs), Maximum Likelihood (ML), and U-Net), taking two grain-producing areas (Site #1 and Site #2) in Haixi Prefecture, Qinghai Province, China, as the research area. The results indicate that employing U-Net on feature-combined sets yielded the highest overall accuracy (OA) of 81.23% and 91.49% for Site #1 and Site #2, respectively, in the single classifier experiments. The E-OAI strategy, compared to the original OAI strategy, boosted the OA by 0.17% to 6.28%. Furthermore, the OAI-MV strategy achieved the highest OA of 86.02% and 95.67% for the respective study sites. This study highlights the distinct strengths of various remote sensing features and classifiers in discerning different crop and vegetation types. Additionally, the proposed OAI-MV and E-OAI strategies effectively harness the benefits of diverse classifiers and multisource remote sensing features, significantly enhancing the accuracy of crop/vegetation classification. [ABSTRACT FROM AUTHOR]

Quantum yield illustrates the efficiency that a fluorophore converts the excitation light into fluorescence emission. The quantum yield of carbon quantum dots (CQDs) can be altered via precursors, fabrication conditions, chemical doping, and surface modifications. In this study, CQDs were first fabricated from whole-meal bread using a chemical-free hydrothermal route, and a low quantum yield (0.81%) was obtained. The combination of whole-meal bread, soybean flour, and lemon juice generated CQDs with almost four folds of enhancement in quantum yield. Detailed characterization suggested that these CQDs were subjected to more complete hydrothermal reactions and had zwitterionic surfaces. The CQDs could selectively detect Cr (VI) ions with a limit of detection (LOD) of 8 ppm. This study shows that the enhancement of the quantum yield of CQDs does not need chemicals, and it is achievable with food precursors. [ABSTRACT FROM AUTHOR]

The keyword extraction of patents is crucial for technicians to master the trends of technology. Traditional keyword extraction approaches only handle short text like title or claims, but ignore the comprehensive meaning of the description. This paper proposes a novel patent keyword extraction method based on corpus classification (PKECC), which simulates the patent understanding methods of human patent examiners. First of all, a corpus classification model based on multi-level attention mechanism adopts the Bert model and hierarchical attention mechanism to classify the sentences of patent description into four parts including technical field, technical problem, technical solution, and technical effect. Then, the proposed keyword extraction method based on the fusion of BiLSTM and CRF is incorporated to extract keywords from the four parts. The proposed PKECC simulates understanding style of patent examiner by extracting keywords from the description. Meanwhile, PKECC may reduce the complexity of extracting keywords from a long text and improve the accuracy of keyword extraction. The proposed PKECC is compared with 5 traditional or state-of-the-art models and achieves better accuracy, F1 score and recall rate; its recall rate is above 62%, its accuracy reaches over 84%, and the F1 score arrives at 69%. In addition, the experimental results shows the proposed PKECC has a better universality in keyword extraction. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) ranks as the third most prevalent global malignancy, marked by significant metastasis and post-surgical recurrence, posing formidable challenges to treatment efficacy. The integration of oligonucleotides with chemotherapeutic drugs emerges as a promising strategy for synergistic CRC therapy. The nanoformulation, lipid nanoparticle (LNP), presents the capability to achieve co-delivery of oligonucleotides and chemotherapeutic drugs for cancer therapy. In this study, we constructed lipid nanoparticles, termed as LNP-I-V by microfluidics to co-deliver oligonucleotides miR159 mimics (VDX05001SI) and irinotecan (IRT), demonstrating effective treatment of CRC both in vitro and in vivo. The LNP-I-V exhibited a particle size of 118.67 ± 1.27 nm, ensuring excellent stability and targeting delivery to tumor tissues, where it was internalized and escaped from the endosome with a pH-sensitive profile. Ultimately, LNP-I-V significantly inhibited CRC growth, extended the survival of tumor-bearing mice, and displayed favorable safety profiles. Thus, LNP-I-V held promise as an innovative platform to combine gene therapy and chemotherapy for improving CRC treatment. [ABSTRACT FROM AUTHOR]

Bridges are a critical component of transportation infrastructure, playing a vital role in connectivity. The safe operation of bridges demands significant resource and capital investment, particularly as the operation phase is the most extended period in a bridge's life cycle. Therefore, the efficient allocation of resources and funds is crucial for the maintenance and repair of bridges. This study addresses the need to predict changes in bridge condition over time. The commonly used state-based Markov chain method for bridge condition rating prediction is straightforward but limited by its assumptions of homogeneity and memorylessness. To improve upon this, we propose a novel method that integrates an Elman neural network with a Markov chain to predict the bridge condition rating. Initially, the ReliefF algorithm conducts a sensitivity analysis on bridge features to obtain the importance ranking of these features that affect the bridge condition. Next, six significant features are selected for data classification: bridge age, average daily truck traffic volume, material type, skew angle between bridges and roads, bridge deck structure type, and bridge type. The Elman neural network is then trained to train a prediction model for bridge condition ratings using the classified data, which can predict the condition levels of bridges. The Markov chain's transition probability matrix is derived using a genetic algorithm to match the deterioration curve predicted by the Elman neural network. This proposed method, when applied to actual bridge data, demonstrates its effectiveness as evidenced by the condition rating of an actual bridge. [ABSTRACT FROM AUTHOR]

Simple Summary: Whirligig beetles inhabit both fresh and brackish waters and possess a pair of split compound eyes. The dorsal eyes are situated above the water surface, whereas the ventral eyes are submerged beneath the water. Due to the difference in optical environments between water and air, we expected a difference in visual features and signal processing between the dorsal and ventral eyes. Using scanning electron microscopy, transmission electron microscopy, and microcomputed tomography, we investigated the functional modifications of different features of the split compound eyes of Dineutus mellyi (Coleoptera: Gyrinidae). Both dorsal and ventral parts of the split compound eyes of D. mellyi are the superposition type, with the ommatidium of dorsal and ventral eyes comprised of a laminated corneal lens, bullet-shaped crystalline cone, upper distal rhabdom, a clear zone and lower distal rhabdom, a basal rhabdom, and an eight retinular cell just above the basement membrane. In contrast to the dorsal eyes, ventral eyes are characterized by a higher field of vision but exhibit similar spatial resolution. The functional anatomy of the split compound eyes of whirligig beetles Dineutus mellyi (Coleoptera: Gyrinidae) was examined by advanced microscopy and microcomputed tomography. We report the first 3D visualization and analysis of the split compound eyes. On average, the dorsal and ventral eyes contain 1913 ± 44.5 facets and 3099 ± 86.2 facets, respectively. The larger area of ventral eyes ensures a higher field of vision underwater. The ommatidium of the split compound eyes is made up of laminated cornea lenses that offer protection against mechanical injuries, bullet-shaped crystalline cones that guide light to the photoreceptive regions, and screening pigments that ensure directional light passage. The photoreceptive elements, made up of eight retinular cells, exhibit a tri-tiered rhabdom structure, including the upper distal rhabdom, a clear zone that ensures maximum light passage, and an enlarged lower distal rhabdom that ensures optimal photon capture. [ABSTRACT FROM AUTHOR]

Rice effective panicle is a major trait for grain yield and is affected by both the genetic tiller numbers and the early tillering vigor (ETV) traits to survive environmental adversities. The mechanism behind tiller bud formation has been well described, while the genes and the molecular mechanism underlying rice-regulating ETV traits are unclear. In this study, the candidate genes in regulating ETV traits have been sought by quantitative trait locus (QTL) mapping and bulk-segregation analysis by resequencing method (BSA-seq) conjoint analysis using rice backcross inbred line (BIL) populations, which were cultivated as late-season rice of double-cropping rice systems. By QTL mapping, seven QTLs were detected on chromosomes 1, 3, 4, and 9, with the logarithm of the odds (LOD) values ranging from 3.52 to 7.57 and explained 3.23% to 12.98% of the observed phenotypic variance. By BSA-seq analysis, seven QTLs on chromosomes 1, 2, 4, 5, 7, and 9 were identified using single-nucleotide polymorphism (SNP) and insertions/deletions (InDel) index algorithm and Euclidean distance (ED) algorithm. The overlapping QTL resulting from QTL mapping and BSA-seq analysis was shown in a 1.39 Mb interval on chromosome 4. In the overlap interval, six genes, including the functional unknown genes Os04g0455650, Os04g0470901, Os04g0500600, and ethylene-insensitive 3 (Os04g0456900), sialyltransferase family domain containing protein (Os04g0506800), and ATOZI1 (Os04g0497300), showed the differential expression between ETV rice lines and late tillering vigor (LTV) rice lines and have a missense base mutation in the genomic DNA sequences of the parents. We speculate that the six genes are the candidate genes regulating the ETV trait in rice, which provides a research basis for revealing the molecular mechanism behind the ETV traits in rice. [ABSTRACT FROM AUTHOR]

Fiber-chip edge couplers can minimize mode mismatch in integrated lithium niobate (LiNbO3) photonics via facilitating broad optical bandwidth coupling between optical fibers and waveguide circuits. We designed a high-efficiency multi-tip edge coupler utilizing the lithium niobate on insulator (LNOI) platform for achieving superior fiber-to-chip coupling. The device comprises a bilayer LN inversely tapered waveguide, three 3D inversely tapered waveguides, and a silicon oxynitride (SiON) cladding waveguide (CLDWG). Finite difference method (FDM) and eigenmode expansion (EME) simulations were utilized to simulate and optimize the edge coupler structure specifically within the 1550 nm band. This coupler demonstrates a low fiber-chip coupling loss of 0.0682/0.0958 dB/facet for TE/TM mode at 1550 nm when interfaced with a commercially cleaved single-mode fiber (SMF) with a mode field diameter (MFD) of approximately 8.2 μm. Moreover, the 1 dB bandwidth of the coupler is 270 nm for the TE mode and 288 nm for the TM mode. Notably, the coupler exhibits a relatively large tolerance for optical misalignment owing to its large mode spot size of up to 4 μm. Given its ultra-low loss, high-efficiency ultra-broadband capabilities, and substantial tolerance features, this proposed device provides a paradigm for fiber-to-chip edge coupling within lithium niobate photonics. [ABSTRACT FROM AUTHOR]

Citrus plants are prone to phosphorus (P) deficiency, especially in acidic soil, making them more dependent on root-associated endophytic fungi for growth and development. Beni-Madonna, a hybrid of Citrus nanko × C. amakusa, is a citrus known as "tangor" that is highly popular in China and other parts of the world due to its deep red color and jelly-like flesh. In this study, the inoculation response to two arbuscular mycorrhizal fungi (Diversispora versiformis, Dv; Funneliformis mosseae, Fm) and an endophytic fungus (Serendipita indica, Si) with regard to the growth, leaf gas exchange, light energy efficiency, P levels, acid phosphatase activity, and expression of the purple acid phosphatase (PAP) and phosphate transporter (PT) genes through a potted experiment using Beni-Madonna (tangor) citrus plants grafted on trifoliate orange (Poncirus trifoliata) was studied. Two years following inoculation, the root fungal colonization rates of inoculated plants were significantly increased, accompanied by an increase in plant height and stem diameter, with Si presenting the best effect. Fungal inoculations also significantly increased the leaf chlorophyll index, nitrogen-balance index, photosynthesis rate, stomatal conductance, transpiration rate, photosynthetic efficiency, and quantum yield of PSII, while it reduced photoinhibition and heat dissipation, with Si having the best effect on light energy efficiency. Si significantly increased leaf and root P levels, as well as root CsPAP1‒3, CsPT2, CsPT3, and CsPT7 expression and soil acid phosphatase activity; Fm in mycorrhizal fungi significantly increased leaf and root P levels, as well as root CsPT1 and CsPT7 expression and root/soil acid phosphatase activity. These observations suggested an advantage of Si over the other two AMF in terms of improved plant growth and P acquisition, while Fm displayed prominent effects on increased photosynthetic efficiency. [ABSTRACT FROM AUTHOR]