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This paper provides a numerical analysis of the topological valley kink states along both zigzag and armchair domain walls of a dielectric two-dimensional photonic crystal (PC), considering the photonic energy band folding mechanism. By engineering the side length of triangular holes in a honeycomb PC, we created inequivalent valleys in the momentum space. We utilized two adjacent valley PCs with inverted structures to induce a topological transition of the TE mode energy band as it crossed the interface. Further research into the projected energy bands along both zigzag and armchair directions revealed that topologically protected valley kink states can be supported by both configurations. The zigzag interface enabled valley waveguides to transport chiral optical fields at the 0°, 60°, and 120° bending angles, while maintaining their backscattering immune properties. The armchair interface, on the other hand, supported the straight propagation. By combining both armchair and zigzag interfaces, the valley waveguide can facilitate bending propagation at 90° and 180°, while also enabling the equal splitting of chiral fields at the intersection between these two interfaces. Our analyzation can be helpful to improve the applications of valley waveguides in integrated photonics. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to understand the health of workers exposed to occupational noise and explore the influencing factors related to workers' health, especially the impact of noise on workers' hearing. This work can provide a basis for formulating relevant measures for occupational noise prevention and control in the future. Methods: On the basis of the key occupational disease monitoring project in Chongqing, China, in 2021, the data of 1125 workers exposed to occupational noise were analyzed. Data included demographic information, occupational history, clinical physical examination information, and noise detection information of the working environment. Chi-square test and multifactorial logistic regression were used for statistical analysis. Results: The prevalence rates of abnormal electrocardiogram (ECG), blood pressure (BP), and pure tone audiometry (PTA) were 21.9% (246/1125), 27.8% (313/1125), and 18.0% (202/1125), respectively. Male workers accounted for 78.8%. Compared with male workers, female workers had a lower prevalence of abnormal PTA (OR = 0.28, 95% CI = 0.16–0.50). Workers working in medium enterprises had a lower prevalence of abnormal BP than workers in micro enterprises (OR = 0.36, 95% CI = 0.19–0.66). The prevalence of abnormal BP and PTA of workers increased with age. After adjusting for age, sex, and body mass index, the prevalence of abnormal ECG of mining workers was higher than that of manufacturing workers (OR = 1.54, 95% CI = 1.07–2.24), and the prevalence of abnormal PTA had a rising trend with the increase in noise exposure value. Conclusion: Noise-exposed workers have a high prevalence of abnormal ECG, BP, and PTA, and factors such as age, enterprise size, and workplace noise exposure are correlated with the aberrant health of workers. Governments, enterprises, and individuals need to attach great importance to the possible adverse effects of noise. They must also actively adopt various effective measures to protect the occupational safety and health of workers. [ABSTRACT FROM AUTHOR]

Background: Scoliosis is a high incidence disease that endangers the physical and mental health of adolescents. Traction therapy, as a conservative treatment plan, is helpful to improve the recovery speed of patients by studying the influence of different traction factors on the therapeutic effect. Methods: Based on the thin layer CT data of the lumbar spine of a 16-year-old patient with scoliosis, Mimics21.0 was used to extract the 3D digital model, and Geomagic Wrap2021 was used to perform the smooth surface. After that, SolidWorks was used to manually construct the structures, such as the intervertebral disc, and Ansys17.0 was used to add constraints, ligaments, and other features. Three-factor ANOVA was carried out after an orthogonal experiment that considered traction mode, traction angle, and traction force was finished. Results: ① A three-dimensional biomechanical model of lumbar scoliosis was created. ② The model's correctness was confirmed by comparing it to the corpse and other finite element models, as well as by verifying it under a range of working settings. ③ Traction force (P = 0.000), traction angle (P = 0.000), the interaction between traction force and traction angle (P = 0.000), and the interaction between traction mode and traction angle (P = 0.045) were all significant. ④ The interaction between traction force and traction angle has the most significant effect on Cobb, and traction with a certain angle is better than traditional axial traction. ⑤ Traction mode is not significant, but the interaction between traction mode and traction angle is significant. Conclusions: A certain angle of traction can aid in improving outcomes and the traction force can be suitably decreased in the clinical formulation of the traction plan. The uniformity of correcting effect is more favorable when higher fixation techniques like positive suspension or traction bed traction are used, as opposed to overhanging traction. [ABSTRACT FROM AUTHOR]

This paper demonstrates the on‐chip terahertz (THz) helical antenna based on metal self‐rolled‐up membrane (M‐SRuM) nanotechnology, which utilizes the residual stress in multilayer metal membrane deposited by electron beam (E‐beam) evaporation to provide the rolling force and to form the radiation body of the helical antenna. Precise design method is proposed based on multi‐physics modeling for mechanical and electrical analysis, and the two operating modes of on‐chip helical antenna are modeled and analyzed. The test results show that the normal mode of self‐rolled‐up THz helical antenna is able to operate at frequency as high as 0.223 THz with the corresponding impedance bandwidth of 13 GHz. [ABSTRACT FROM AUTHOR]

Background: Senecavirus A (SVA), identified in 2002, is known to cause porcine idiopathic vesicular disease (PIVD), which presents with symptoms resembling other vesicular diseases. This similarity complicates field diagnosis. Conventional molecular diagnostic techniques are limited by their cost, sensitivity, and requirement for complicated instrumentation. Therefore, developing an effective and accurate diagnostic method is crucial for timely identification and isolation of affected pigs, thereby preventing further disease spread. Methods: In this study, we developed a highly-specific and ultra-sensitive SVA detection method powered by CRISPR/Cas12a. To enhance the availability in laboratories with varied equipment conditions, microplate reader and ultraviolet light transilluminator were introduced. Moreover, PCR amplification has also been incorporated into this method to improve sensitivity. The specificity and sensitivity of this method were determined following the preparation of the recombinant Cas12a protein and optimization of the CRISPR/Cas12a-based trans-cleavage system. Results: The method demonstrated no cross-reactivity with ten kinds of viruses of swine. The minimum template concentration required to activate substantial trans-cleavage activity was determined to be 106 copies/µL of SVA templates. However, when PCR amplification was incorporated, the method achieved a detection limit of one copy of SVA templates per reaction. It also exhibited 100% accuracy in simulated sample testing. The complete testing process does not exceed three hours. Conclusions: Importantly, this method utilizes standard laboratory equipment, making it accessible for use in resource-limited settings and facilitating widespread and ultra-sensitive screening during epidemics. Overall, the development of this method not only broadens the array of tools available for detecting SVA but also holds significant promise for controlling the spread of PIVD. [ABSTRACT FROM AUTHOR]

ObjectiveMethodsResultsConclusionThis study aimed to find out the efficacy of using Hypertonic saline solution (HSS) over mannitol in the management of TBI by comparing their performance in improving different outcomes.Electronic databases were searched for randomized controlled trials (RCTs) assessing the impact of HSS vs. mannitol on ICP in patients who suffered TBI. Outcomes of interest were mortality, neurologic functional outcomes, risk ratio (RR) of successful ICP treatment, reduction in ICP after 30–60 and 90–120 min, improvement in cerebral perfusion pressure (CPP) at 30–60 and 90–120 min, and also treatment failure. Evaluations were reported as RR or mean difference (MD) with 95% confidence intervals (CIs) using weighted random-effects models.The analysis included 624 patients from 15 RCTs. HSS infusion had a significant impact on the improvement of CPP at 30–60 min [MD = 5.54, 95% CI (3.04, 8.03),p < 0.001] compared to mannitol. However, results yielded no significant difference between HSS and mannitol in terms of mortality, neurologic functional outcomes, successful ICP treatment, reduction in ICP after 30–60 min and 90–120 min, improvement in CPP at 90–120 min, and treatment failure.HSS and mannitol are both effective treatments for elevated ICP due to TBI. However, further research is required to derive a better comparison. [ABSTRACT FROM AUTHOR]

mRNA vaccines are entering a period of rapid development. However, their synthesis is still plagued by challenges related to mRNA impurities and fragments (incomplete mRNA). Most impurities of mRNA products transcribed in vitro are mRNA fragments. Only full-length mRNA transcripts containing both a 5′-cap and a 3′-poly(A) structure are viable for in vivo expression. Therefore, RNA fragments are the primary product-related impurities that significantly hinder mRNA efficacy and must be effectively controlled; these species are believed to originate from either mRNA hydrolysis or premature transcriptional termination. In the manufacturing of commercial mRNA vaccines, T7 RNA polymerase-catalyzed in vitro transcription (IVT) synthesis is a well-established method for synthesizing long RNA transcripts. This study identified a pivotal domain on the T7 RNA polymerase that is associated with erroneous mRNA release. By leveraging the advantageous properties of a T7 RNA polymerase mutant and precisely optimized IVT process parameters, we successfully achieved an mRNA integrity exceeding 91%, thereby further unlocking the immense potential of mRNA therapeutics. [ABSTRACT FROM AUTHOR]

Challenges in enhancing the multiclass segmentation of remotely sensed data include expensive and scarce labeled samples, complex geo-surface scenes, and resulting biases. The intricate nature of geographical surfaces, comprising varying elements and features, introduces significant complexity to the task of segmentation. The limited label data used to train segmentation models may exhibit biases due to imbalances or the inadequate representation of certain surface types or features. For applications like land use/cover monitoring, the assumption of evenly distributed simple random sampling may be not satisfied due to spatial stratified heterogeneity, introducing biases that can adversely impact the model's ability to generalize effectively across diverse geographical areas. We introduced two statistical indicators to encode the complexity of geo-features under multiclass scenes and designed a corresponding optimal sampling scheme to select representative samples to reduce sampling bias during machine learning model training, especially that of deep learning models. The results of the complexity scores showed that the entropy-based and gray-based indicators effectively detected the complexity from geo-surface scenes: the entropy-based indicator was sensitive to the boundaries of different classes and the contours of geographical objects, while the Moran's I indicator had a better performance in identifying the spatial structure information of geographical objects in remote sensing images. According to the complexity scores, the optimal sampling methods appropriately adapted the distribution of the training samples to the geo-context and enhanced their representativeness relative to the population. The single-score optimal sampling method achieved the highest improvement in DeepLab-V3 (increasing pixel accuracy by 0.3% and MIoU by 5.5%), and the multi-score optimal sampling method achieved the highest improvement in SegFormer (increasing ACC by 0.2% and MIoU by 2.4%). These findings carry significant implications for quantifying the complexity of geo-surface scenes and hence can enhance the semantic segmentation of high-resolution remote sensing images with less sampling bias. [ABSTRACT FROM AUTHOR]

Background Many studies have examined patient-related factors affecting adjuvant hormone therapy adherence in patients with breast cancer. Our study aimed to examine associations of family-related factors with adjuvant hormone therapy discontinuation and breast cancer–specific mortality. Methods By cross-linking 7 Swedish health registers, we performed a cohort study that included all patients with breast cancer who initiated adjuvant hormone therapy during 2006-2019 in Sweden (N = 10 701). A group-based multitrajectory model was used to identify familial adversity groups based on 3 dimensions: material deprivation, negative family dynamics, and loss or threat of loss. Cox proportional hazard models were used to investigate associations of familial adversity with hormone therapy discontinuation and breast cancer–specific mortality. Results We identified 5 distinctive familial adversity groups among the cohort participants. Compared with women who had low familial adversity, higher risks to discontinue adjuvant hormone therapy were observed among women with material deprivation (hazard ratio [HR] = 1.31, 95% confidence interval [CI] = 1.20 to 1.43), negative family dynamics (HR = 1.16, 95% CI = 1.06 to 1.28), loss or threat of loss (HR = 1.15, 95% CI = 1.00 to 1.32), or high familial adversity (HR = 1.53, 95% CI = 1.40 to 1.68). Furthermore, women with material deprivation (HR = 1.37, 95% CI = 1.05 to 1.79), negative family dynamics (HR = 1.41, 95% CI = 1.01 to 1.97), or high adversity (HR = 1.67, 95% CI = 1.26 to 2.23) were at higher risk of dying from breast cancer. Conclusion Familial adversity is associated with a higher risk of adjuvant hormone therapy discontinuation and breast cancer–specific mortality. Family-related factors identified in our study may help identify high-risk patients for interventions to prevent treatment discontinuation and subsequently improve breast cancer outcomes. [ABSTRACT FROM AUTHOR]

Structured light can be encoded to carry information for free‐space optical communications with an extended degree of freedom to increase the capacity, however, the accuracy issue along with capacity increase is one of the biggest challenges that prevent practical applications. To achieve high accuracy with high capacity by a simple method, they propose the spatial nonlinear conversion of structured light into a communication network, especially, realizing an ultra‐high‐accuracy point‐to‐multipoint (PtoMP) information transmission link. A series of coherently superposed spatial modes and their spatial nonlinear conversion states are used as information carriers to replace the prior orbital angular momentum beams and greatly expand channel capacity within quite low spatial mode order. Through the spatial nonlinear conversion of simple dual‐mode superposition and a very basic neural network for machine learning‐based recognition, as high as 99.5% accuracy for more than 500 modes is obtained. By a combination of diffuse reflection screens and multiple CCDs, the large observation angle PtoMP information transmission is also proved to be feasible. This work paves the way for practical large‐scale multi‐party information networks using structured light. [ABSTRACT FROM AUTHOR]

Incorporating green tea powder (GTP) into wheat flour–based noodles can significantly improve nutritional value. So, this study investigated the effects of GTP (0%, 0.5%, 1%, 1.5%, and 2.0%) on the quality properties of dried green tea noodles (DGTN) and cooking‐induced changes to phenolic compounds. Mixolab analysis of wheat flour with GTP showed more water absorption of dough, and the developed dough had a firmer structure. GTP markedly increased the toughness of the noodle sheet. DGTN fortified with GTP showed more stable textural properties during cooking and storage, representing higher hardness and tensile strength. The viscosity and thermal properties of DGTN showed that GTP affected the gelatinization and retrogradation behavior of starch, which were closely related to the textural properties. Overall, DGTN prepared with 1.5% GTP showed better quality properties. However, ultra‐performance liquid chromatography‐time (UPLC/Q‐TOF‐mass spectrometry [MS]/MS) analysis showed that cooking by boiling significantly decreased phenolic content in 1.5% DGTN; further analysis revealed that the thermal degradation is a key factor in the loss of polyphenols. Therefore, further studies are necessary to focus on the mechanism of cooking‐induced polyphenol loss, which is of great significance for improving the nutritional value of cooked DGTN. [ABSTRACT FROM AUTHOR]

Circularly polarized light (CPL) detection is of great significance in various applications such as drug identification, sensing and imaging. Atomically precise chiral metal nanoclusters with intense circular dichroism (CD) signals are promising candidates for CPL detection, which can further facilitate device miniaturization and integration. Herein, we report the preparation of a pair of optically active chiral silver nanoclusters [Ag7(R/S‐DMA)2(dpppy)3] (BF4)3 (R/S‐Ag7) for direct CPL detection. The crystal structure and molecular formula of R/S‐Ag7 clusters are confirmed by single‐crystal X‐ray diffraction and high‐resolution mass spectrometry. R/S‐Ag7 clusters exhibit strong CD spectra and CPL both in solution and solid states. When used as the photoactive materials in photodetectors, R/S‐Ag7 enables effective discrimination between left‐handed circularly polarized and right‐handed circularly polarized light at 520 nm with short response time, high responsivity and considerable discrimination ratio. This study is the first report on using atomically precise chiral metal nanoclusters for CPL detection. [ABSTRACT FROM AUTHOR]

The single‐unit monomer insertion (SUMI), derived from living/controlled polymerization, can be directly functionalized at the end or within the chain of polymers prepared by living/controlled polymerization, offering potential applications in the preparation of polymers with complex architectures. Many scenarios demand the simultaneous incorporation of monomers suitable for different polymerization methods into complex polymers. Therefore, it becomes imperative to utilize SUMI technologies with diverse mechanisms, especially those that are compatible with each other. Here, we reported the orthogonal SUMI technique, seamlessly combining radical and cationic SUMI approaches. Through the careful optimization of monomer and chain transfer agent pairs and adjustments to reaction conditions, we can efficiently execute both radical and cationic SUMI processes in one pot without mutual interference. The utilization of orthogonal SUMI pairs facilitates the integration of radical and cationic reversible addition‐fragmentation chain transfer (RAFT) polymerization in various configurations. This flexibility enables the synthesis of diblock, triblock, and star polymers that incorporate both cationically and radically polymerizable monomers. Moreover, we have successfully implemented a mixing mechanism of free radicals and cations in RAFT step‐growth polymerization, resulting in the creation of a side‐chain sequence‐controlled polymer brushes. [ABSTRACT FROM AUTHOR]

To overcome the issues of the existing properties and the non-configurable supervisory control and data acquisition (SCADA) architecture, this paper proposes an IoT-centered open-source SCADA system for monitoring photovoltaic (PV) systems. The system consists of three voltage sensors and three current sensors for data accumulation from the PV panel, the battery, and the load. As a part of the system design, a relay is used that controls the load remotely. An ESP32-E microcontroller transmits the collected data to a Banana Pi M4 Berry (BPI-M4 Berry) through the Message Queuing Telemetry Transport (MQTT) protocol over a privately established communication channel using Wi-Fi. The ESP32-E is configured as the MQTT publisher and the BPI-M4 Berry serves as the MQTT broker. Locally installed on the BPI-M4 Berry, the Node-RED platform creates highly customizable dashboards as human–machine interfaces (HMIs) to achieve real-time monitoring of the PV system. The proposed system was successfully tested to collect the PV system voltage/current/power data and to control the load in a supervisory way under a laboratory setup. The complete SCADA architecture details and test results for the PV system data during the total eclipse on 8 April 2024 and another day are presented in this paper. [ABSTRACT FROM AUTHOR]

Alkylamines with different chain lengths including n-butylamine, n-hexylamine, and n-octylamine, are applied to regulate the CsPbIBr2 perovskite film quality by strain engineering. The status of residual strains is controllably modulated, resulting in improved efficiency and stability of carbon-based hole-transport-material free CsPbIBr2 perovskite solar cells. [ABSTRACT FROM AUTHOR]

Children's interpretations of parenting behaviors offer valuable insights into cultural meanings of parenting. This study examined how Chinese urban and rural children interpreted six different types of parental responses to children's negative emotions (PRCNE), which have traditionally been identified as supportive (e.g., emotion‐focused responses, problem‐focused responses, and expressive encouragement) versus nonsupportive ones (e.g., minimization, parental distress, punitive responses) in Western cultures. Based on surveyed samples of 976 children, demographically matched samples of 102 urban (Mage = 14.23 years) and 100 rural (Mage = 14.38 years) children were generated for analysis, using propensity score matching (PSM). Results revealed that compared with rural children, urban children rated problem‐focused responses as more normative, whereas parental distress and punitive responses as less normative. Additionally, urban children evaluated emotion‐focused responses, problem‐focused responses, expressive encouragement, and minimization as less negative, and parental distress as less positive than rural children. In urban communities, emotion‐focused responses, problem‐focused responses, and encouragement were evaluated most positively and least negatively, followed by minimization, and lastly parental distress and punitive responses. In rural communities, emotion‐focused responses and problem‐focused responses were evaluated most positively and least negatively, followed by encouragement and minimization, and lastly parental distress and punitive responses. The findings highlight the diverse interpretations children have towards PRCNE across different cultural contexts. [ABSTRACT FROM AUTHOR]

This paper presents a massively parallel approach of the multilevel fast multipole algorithm (PMLFMA) on homegrown many-core SW26010 cluster of China, noted as (SW-PMLFMA), for 3-D electromagnetic scattering problems. In this approach, the multilevel fast multipole algorithm (MLFMA) octree is first partitioned among management processing elements (MPEs) of SW26010 processors following the ternary partitioning scheme using the message passing interface (MPI). Then, the computationally intensive parts of the PMLFMA on each MPI process, matrix filling, aggregation and disaggregation are accelerated by using all the 64 computing processing elements (CPEs) in the same core group of the MPE via the Athread parallel programming model. Different parallelization strategies are designed for many-core accelerators to ensure a high computational throughput. In coincidence with the special characteristic of local Lagrange interpolation, the compressed sparse row (CSR) and the compressed sparse column (CSC) sparse matrix storage format is used for storing interpolation and anterpolation matrices, respectively, together with a specially designed cache mechanism of hybrid dynamic and static buffers using the scratchpad memory (SPM) to improve data access efficiency. Numerical results are included to demonstrate the efficiency and versatility of the proposed method. The proposed parallel scheme is shown to have excellent speedup. [ABSTRACT FROM AUTHOR]

Introduction: Regorafenib remains the standard and widely used second‐line strategy for advanced hepatocellular carcinoma (HCC). There is still a lack of large‐scale multicenter real‐world evidence concerning the concurrent use of regorafenib with immune checkpoint inhibitors (ICI). This study aims to evaluate whether combining regorafenib with ICI provides greater clinical benefit than regorafenib monotherapy as second‐line therapy for advanced HCC under real‐world circumstances. Patients and Methods: The study included 208 patients from five medical facilities. One hundred forty‐three patients received regorafenib plus ICI combination therapy, while 65 patients received regorafenib monotherapy. Propensity score matching (PSM) analysis was employed. Results: The regorafenib plus ICI group demonstrated significantly higher objective response rate (24.3% vs. 10.3%, after PSM, p = 0.030) and disease control rate (79.4% vs. 50.0%, after PSM, p < 0.001) compared to the regorafenib monotherapy group based on mRECIST criteria. Median progression‐free survival (7.9 vs. 3.2 months, after PSM, p < 0.001) and overall survival (25.6 vs. 16.4 months, p = 0.010, after PSM) were also considerably longer in the regorafenib plus ICI group. The incidence of Grades 3–4 treatment‐related adverse events (TRAEs) was marginally greater in the regorafenib plus ICI group than in the regorafenib group (23.8% vs. 20.0%, p = 0.546). Notably, there were no instances of treatment‐related mortality or emergence of new TRAEs in any treatment group. Conclusion: The combination of regorafenib and ICI shows potential as a viable second‐line treatment for advanced HCC, exhibiting favorable efficacy while maintaining a tolerable safety profile in contrast to regorafenib monotherapy. [ABSTRACT FROM AUTHOR]

Previous studies have shown that sampling processing and identification methods for neural networks damage identification in multi-channel and multi-source structural dynamic response data exhibit diversity, and the robustness and generalization issues of the model have not been effectively solved. This paper proposes a sample preprocessing technique and mixed training method suitable for multi-channel and multi-source dynamic response data to optimize the current structural damage identification methods based on neural networks. Through multi-dimensional discrete autocorrelation processing and Fourier transform, the preprocessed datasets from multiple sensors with multi-channel can access multi-channel CNN. Furthermore, the measured datasets from the actual structures are mixed with numerical simulation datasets before being used for neural network model training to address the model calibration and the imbalanced sample size under each classification label. The results of extensive model experiments and finite element verification of specimens show that the method performs outstandingly in detecting and identifying damage to simply supported beam structures using multi-channel CNN. The neural network model trained with preprocessed samples exhibits excellent robustness. The model using the mixed training method still performs well in identifying the accuracy of damage location and degree in simply supported beam structures after changing beam section and initial excitation. The method has certain generalization ability in detecting unknown damage in simply supported beam structures. [ABSTRACT FROM AUTHOR]

A dual-parameter sensor for simultaneous strain and temperature measurement is proposed and demonstrated based on the introduction of higher-order modes in a single-mode-multimode-single-mode (SMS) structure cascaded with a Fabry–Perot (FP) cavity as a compact and low-cost fiber optic sensor. In this structure, a multimode fiber is spliced between two single-mode fibers, and the single-mode fiber at the other end is fusion spliced to the HF-corroded single-mode fiber to form the SMS-FP cascade structure. Light transmitted from the multimode fiber to the FP cavity can couple light into the cladding, introducing higher-order modes into modal interference. Moreover, multiple-beam interference generates spectra. The experimental results indicate that the sensor performs effectively within the range of 150∘C–250∘C and 0–875 μ ε. The strain sensitivities of SMS and FP were found to be −2.45 and −2.34 pm/ μ ε , respectively, and their temperature sensitivities are 11.85 and 5.59 pm/∘C, respectively. The interesting features of the sensor include good operating linearity, compact size, high sensitivity, simple structure and low cost. [ABSTRACT FROM AUTHOR]

Background: Cold stress has negative effects on the growth and health of mammals, and has become a factor restricting livestock development at high latitudes and on plateaus. The gut-liver axis is central to energy metabolism, and the mechanisms by which it regulates host energy metabolism at cold temperatures have rarely been illustrated. In this study, we evaluated the status of glycolipid metabolism and oxidative stress in pigs based on the gut-liver axis and propose that AMP-activated protein kinase (AMPK) is a key target for alleviating energy stress at cold temperatures by dietary fat supplementation. Results: Dietary fat supplementation alleviated the negative effects of cold temperatures on growth performance and digestive enzymes, while hormonal homeostasis was also restored. Moreover, cold temperature exposure increased glucose transport in the jejunum. In contrast, we observed abnormalities in lipid metabolism, which was characterized by the accumulation of bile acids in the ileum and plasma. In addition, the results of the ileal metabolomic analysis were consistent with the energy metabolism measurements in the jejunum, and dietary fat supplementation increased the activity of the mitochondrial respiratory chain and lipid metabolism. As the central nexus of energy metabolism, the state of glycolipid metabolism and oxidative stress in the liver are inconsistent with that in the small intestine. Specifically, we found that cold temperature exposure increased glucose transport in the liver, which fully validates the idea that hormones can act on the liver to regulate glucose output. Additionally, dietary fat supplementation inhibited glucose transport and glycolysis, but increased gluconeogenesis, bile acid cycling, and lipid metabolism. Sustained activation of AMPK, which an energy receptor and regulator, leads to oxidative stress and apoptosis in the liver; dietary fat supplementation alleviates energy stress by reducing AMPK phosphorylation. Conclusions: Cold stress reduced the growth performance and aggravated glycolipid metabolism disorders and oxidative stress damage in pigs. Dietary fat supplementation improved growth performance and alleviated cold temperature-induced energy stress through AMPK-mediated mitochondrial homeostasis. In this study, we highlight the importance of AMPK in dietary fat supplementation-mediated alleviation of host energy stress in response to environmental changes. [ABSTRACT FROM AUTHOR]

Summary Fusarium head blight (FHB) and the presence of mycotoxin deoxynivalenol (DON) pose serious threats to wheat production and food safety worldwide. DON, as a virulence factor, is crucial for the spread of FHB pathogens on plants. However, germplasm resources that are naturally resistant to DON and DON‐producing FHB pathogens are inadequate in plants. Here, detoxifying bacteria genes responsible for DON epimerization were used to enhance the resistance of wheat to mycotoxin DON and FHB pathogens. We characterized the complete pathway and molecular basis leading to the thorough detoxification of DON via epimerization through two sequential reactions in the detoxifying bacterium Devosia sp. D6‐9. Epimerization efficiently eliminates the phytotoxicity of DON and neutralizes the effects of DON as a virulence factor. Notably, co‐expressing of the genes encoding quinoprotein dehydrogenase (QDDH) for DON oxidation in the first reaction step, and aldo‐keto reductase AKR13B2 for 3‐keto‐DON reduction in the second reaction step significantly reduced the accumulation of DON as virulence factor in wheat after the infection of pathogenic Fusarium, and accordingly conferred increased disease resistance to FHB by restricting the spread of pathogenic Fusarium in the transgenic plants. Stable and improved resistance was observed in greenhouse and field conditions over multiple generations. This successful approach presents a promising avenue for enhancing FHB resistance in crops and reducing mycotoxin contents in grains through detoxification of the virulence factor DON by exogenous resistance genes from microbes. [ABSTRACT FROM AUTHOR]

Future industrialization of organic photovoltaics (OPVs) requires OPVs' processing to be more energy‐efficient and streamlined. Currently, only MoO3 and PEDOT:PSS are commonly used as the anode interface layer (AIL). The processing of MoO3 typically involves vacuum thermal evaporation with stringent thickness requirements. PEDOT:PSS necessitates separate processing and thermal annealing at temperatures exceeding 100 °C to eliminate moisture. This work utilized 3,4,5‐trichlorobenzoic acid (3CBA) as the AIL material. The distinct advantage of 3CBA over PEDOT:PSS and MoO3 is the in situ self‐assembly of 3CBA eliminates the need for separate solution processing, thermal evaporation, or thermal annealing. Remarkably, OPV devices incorporating PM6, BTP‐eC9, and the 3CBA AIL exhibited a superior efficiency of 18.2% compared to those with PEDOT:PSS (17.7%). By using nonhalogenated solvent, o‐xylene, to meet industrialization requirements, the devices achieved an exceptional efficiency of 18.8%, the highest reported value among devices with in situ self‐assembled interface layers. Furthermore, semi‐transparent devices with 3CBA displayed higher PCE and AVT values (13.1% and 25.7%) than their PEDOT: PSS counterparts, due to the weak absorption of the 3CBA AIL. This work contributes significantly to the high‐throughput production of OPVs by streamlining the AIL processing. [ABSTRACT FROM AUTHOR]

Accurately obtaining the spatial distribution and planting patterns of crops is very important for agricultural planning and food security. At present, time-series images have been proved to be an effective tool to characterize crop seasonal growth patterns, and identifying crop information by measuring the time-series similarity between unknown classes and known crop phenology curves is also considered to be a useful way. However, the existing methods of selecting feature ignore the connection between each phenological stage of crops and the unique growth rules of the whole phenology, which makes it difficult to select time-series spectral features that are potentially important for crop mapping. In order to make up for this problem, a Whole Phenology-based Spectral Feature Selection (WPS) method was proposed. The aim was to select the time-series feature sets with great differences among winter crops from a large number of spectral features, so as to improve the mapping accuracy of winter rapeseed and winter wheat. Firstly, spectral separability between all classes is calculated. Secondly, the key phenological periods of winter crops were selected according to the importance of temporal features, and the spectral feature sets with high separability were selected according to the key phenological periods. Finally, a Time-weighted Dynamic Time Warping (TWDTW) algorithm was used to generate the winter rapeseed and winter wheat maps of two cities in the middle and lower reaches of the Yangtze River. The mapping accuracy of the two crops is more than 92%, which matches the crop planting area well. The research shows that combining the WPS method with the TWDTW mapping method has great potential to accurately map crop types based on satellite time-series images. [ABSTRACT FROM AUTHOR]

Objective To Chinesize the Nursing Home Care-related Quality of Life Scale (NHC-QoL) and to test its reliability and validity. Methods According to the Brislin model, the NHC-QoL scale was translated into Chinese and cross-cultural debugging was carried out. Using convenience sampling method, 198 elderly people from 4 nursing institutions in Shiyan city were investigated by questionnaire from March to July 2023 to evaluate the reliability and validity of the scale. Results There were 14 items in the Chinese version of NHC-QoL. The content validity index of each item was 0.7-1.0, and the content validity index of the scale was 0.929. Exploratory factor analysis extracted 5 common factors, which could explain 67.914% of the total variation. After discussion within the research group, the common factors were reduced to 2 common factors namely environment and service (11 items) and social interaction (3 items). The total Cronbach's α coefficient of the scale was 0.758 and the test-retest reliability was 0.783. Conclusion The Chinese version of NHC-QoL scale has good reliability and validity and can be used to evaluate the quality of life of the elderly in nursing institutions. [ABSTRACT FROM AUTHOR]

Mangiferin (MGN) is primarily found in the fruits, leaves, and bark of plants of the Anacardiaceae family, including mangoes. MGN exhibits various pharmacological effects, such as protection of the liver and gallbladder, anti-lipid peroxidation, and cancer prevention. This study aimed to investigate the effects of MGN supplementation during in vitro culture (IVC) on the antioxidant capacity of early porcine embryos and the underlying mechanisms involved. Porcine parthenotes in the IVC medium were exposed to different concentrations of MGN (0, 0.01, 0.1, and 1 µM). The addition of 0.1 µM MGN significantly increased the blastocyst formation rate of porcine embryos while reducing the apoptotic index and autophagy. Furthermore, the expression of antioxidation-related (SOD2, GPX1, NRF2, UCHL1), cell pluripotency (SOX2, NANOG), and mitochondria-related (TFAM, PGC1a) genes was upregulated. In contrast, the expression of apoptosis-related (CAS3, BAX) and autophagy-related (LC3B, ATG5) genes decreased after MGN supplementation. These findings suggest that MGN improves early porcine embryonic development by reducing oxidative stress-related genes. [ABSTRACT FROM AUTHOR]

Currently, little is known about the characteristics of polyphenol oxidase from wheat bran, which is closely linked to the browning of wheat product. The wheat PPO was purified by ammonium sulfate precipitation, DEAE-Sepharose ion-exchange column, and Superdex G-75 chromatography column. Purified wheat PPO activity was 11.05-fold higher, its specific activity was 1365.12 U/mg, and its yield was 8.46%. SDS-PAGE showed that the molecular weight of wheat PPO was approximately 21 kDa. Its optimal pH and temperature were 6.5 and 35 °C for catechol as substrate, respectively. Twelve phenolic substrates from wheat and green tea were used for analyzing the substrate specificity. Wheat PPO showed the highest affinity to catechol due to its maximum Vmax (517.55 U·mL−1·min−1) and low Km (6.36 mM) values. Docking analysis revealed strong affinities between catechol, gallic acid, EGCG, and EC with binding energies of −5.28 kcal/mol, −4.65 kcal/mol, −4.21 kcal/mol, and −5.62 kcal/mol, respectively, for PPO. Sodium sulfite, ascorbic acid, and sodium bisulfite dramatically inhibited wheat PPO activity. Cu2+ and Ca2+ at 10 mM were considered potent activators and inhibitors for wheat PPO, respectively. This report provides a theoretical basis for controlling the enzymatic browning of wheat products fortified with green tea. [ABSTRACT FROM AUTHOR]

BACKGROUND: The correlation between the change in foveal thickness measured using optical coherence tomography (OCT) following surgery for infectious endophthalmitis and preoperative and postoperative visual acuity is uncertain, and there are few pertinent studies on this topic. OBJECTIVE: We explored the variations in macular thickness using OCT after emergency vitrectomy for post-cataract infectious endophthalmitis and the relationship between macular thickness with changes in visual function. METHODS: We included 10 cases of post-cataract infectious endophthalmitis. Each patient underwent 25-G vitrectomy. RESULTS: The infection in all 10 patients was under control and visual function improved. Postoperative vitreous humor culture was positive in 8 patients, including 7 cases of coagulase-negative Staphylococcus epidermidis and 1 case of Lactobacillus acidophilus. The average age of these 10 patients was 71.60 ± 8.71 years (P < 0.05, two-tailed). There was no significant correlation between time 2 (the time of onset after cataract surgery) and visual prognosis. The average time 1 (the time of the vitrification surgery caused by the onset of the disease) was 1.45 ± 0.76 days (P < 0.05, two-tailed). The postoperative 3dVA ranged from 0.20 to 3.00, with an average visual acuity of 1.87 ± 1.12, which was superior to the preoperative value (P < 0.01, two-tailed). The correlation between the post3dVA and post 1mVA was significant. The post 1mVA ranged from 0.05 to 2.20, with an average visual acuity of 0.94 ± 0.74 (P < 0.05, two-tailed). The correlation between post 1mVA and post3mVA was significant. Also, paired t -tests comparing preoperative and postoperative visual acuity revealed a significant correlation (P < 0.05, two-tailed). The post3mVA was 0–1.00 with an average visual acuity of 0.44 ± 0.41. The postoperative foveal thickness ranged from 176.00 to 514.00 μ m, with an average thickness of 281.10 ± 113.12 μ m. CONCLUSION: Emergency 25-G minimally invasive vitrectomy can improve visual acuity and decrease the reoperation rate for patients who have acquired post-cataract infectious endophthalmitis. There were significant correlations between age, disease onset to operation time, preoperative and postoperative visual acuity, and postoperative macular thickness. [ABSTRACT FROM AUTHOR]

Researching the structural characteristics of the spatial correlation network of cultivated land utilization ecological efficiency is of great significance to China's food security and agricultural green and low-carbon development. Taking 47 cities (autonomous prefectures) in the upper reaches of the Yangtze River as the research object, the ecological efficiency of cultivated land utilization from 2010 to 2020 was measured based on the unexpected output model (Super SBM), and the spatial correlation matrix was constructed using the revised gravity model. The structural characteristics of the spatial correlation network were analyzed using the social network model (SNA), and finally, the factors affecting the spatial correlation network of cultivated land utilization ecological efficiency in the upper reaches of the Yangtze River were analyzed through the quadratic assignment procedure (QAP) model. The results show that: (1) the ecological efficiency of cultivated land utilization in the upper reaches of the Yangtze River has been increasing year by year, but the overall level is low, and there is a large gap among provinces. Sichuan Province has the highest average value of 0.605, and Yunnan Province has the lowest average value of 0.359. (2) The ecological efficiency of cultivated land utilization in the upper reaches of the Yangtze River has broken through the provincial boundaries and has formed an obvious spatial correlation network, but the overall density is low, and the network is still relatively loose, needing further development and improvement. Chengdu, Yibin, Luzhou, and other cities are located in the center of the network and have formed four cohesive subgroups. (3)The differences in the level of agricultural economic development, the rural per capita disposable income, the differences in agricultural mechanization intensity, the regional population differences, and spatial adjacency have an impact on the spatial network of ecological efficiency of cultivated land utilization in the upper reaches of the Yangtze River. The difference in the level of agricultural economic development, the rural per capita disposable income, and the differences in agricultural mechanization intensity are negatively correlated, while the regional population differences are positively correlated with spatial adjacency. [ABSTRACT FROM AUTHOR]

This paper addressed the challenges associated with the complexity, numerous parameters, computational resource demands, and slow processing speed of transformer fault identification models based on deep learning technologies. Sparse convolutional neural network (CNN) approach is proposed for identifying faults related to dissolved gases in oil. Leveraging an improved Gramian angular field, one‐dimensional fault samples are converted into two‐dimensional feature images and data augmentation is implemented to meet the input requirements of deep learning models. Building upon visual geometry group (VGG)19 and residual networks (ResNet)50 networks for fault diagnosis, sparsity techniques are introduced through pruning, the fusion of convolution layers and batch normalization layers, and parameter quantization. Numerical experiments and performance evaluations on dissolved gas in transformer oil fault data demonstrate that the proposed method effectively reduced model complexity, minimized parameter count, conserved computational resources, and improved processing speed while maintaining a considerable level of fault identification accuracy. This made it applicable to edge computing platforms characterized by small form factors and low power consumption in the power industry. [ABSTRACT FROM AUTHOR]

Efflux pumps play important roles in bacterial detoxification and some of them are stress-response elements that are up-regulated when the host is treated with antibiotics. However, efflux pumps that are down-regulated by stimulations are rarely discovered. Herein, we analyzed multiple transcriptome data and discovered a special (Major Facilitator Superfamily) MFS efflux pump, KpsrMFS, from Klebsiella pneumoniae, which was down-regulated when treated with antibiotics or extra carbon sources. Interestingly, overexpression of kpsrmfs resulted in halted cell growth in normal conditions, while the viable cells were rarely affected. The function of KpsrMFS was further analyzed and this efflux pump was determined to be a proton-driven transporter that can reduce the intracellular tetracycline concentration. In normal conditions, the expression of kpsrmfs was at a low level, while artificial overexpression of it led to increased endogenous reactive oxygen species (ROS) production. Moreover, by comparing the functions of adjacent genes of kpsrmfs, we further discovered another four genes that can confer similar phenotypes, indicating a special regulon that regulates cell growth. Our work provides new insights into the roles of efflux pumps and suggests a possible regulon that may regulate cell growth and endogenous ROS levels. [ABSTRACT FROM AUTHOR]

One normal outburst and three mini‐outbursts have been detected by Rossi X‐ray Timing Explorer (RXTE) satellite after 2000 in the well‐known black hole X‐ray binary XTE J1550‐564. In our work, we explored the energy spectral properties of the four outbursts and the three mini‐outbursts retained in the Low/Hard state. The results show that the X‐ray spectra of the three mini‐outbursts are harder than that of normal outburst and have no disk component. In the correlation analysis, the Γ−LX/LEdd$$ \Gamma -{L}_{\mathrm{X}}/{L}_{\mathrm{Edd}} $$ anti‐relationship of the three mini‐outbursts suggested that it may be a result of the incomplete evolutionary success of Shakura‐Sunyaev disk. The whole X‐ray spectral correlation evolution shows well the state transition from the Shakura‐Sunyaev disk to the advection‐dominated accretion flow. We think that the three mini‐outbursts may originated from a small discrete accretion event. [ABSTRACT FROM AUTHOR]

The mini‐outburst of black hole X‐ray binaries (BHXBs) is a re‐bright event of light curve, which is often detected in BHXBs with the low orbital period, such as XTE J1650‐500 (Porb≈7.69±0.02hr$$ {P}_{\mathrm{orb}}\approx 7.69\pm 0.02\kern0.22em \mathrm{hr} $$), GRO J0422+32 (Porb≈5.091850±0.000005hr$$ {P}_{\mathrm{orb}}\approx 5.091850\pm 0.000005\kern0.22em \mathrm{hr} $$) and Swift J1753.5‐0127 (Porb≈3.244±0.001hr$$ {P}_{\mathrm{orb}}\approx 3.244\pm 0.001\kern0.22em \mathrm{hr} $$). Because of its low X‐ray luminosity, the physics properties of mini‐outburst is still unclear. GX 339‐4 is a famous BHXBs with the orbital period Porb=16.9hr$$ {P}_{\mathrm{orb}}=16.9\kern0.22em \mathrm{hr} $$ and present many normal outburst and failed outburst over the past decades. However, the mini‐outburst is not still detected in GX 339‐4. In this work, using the Rossi X‐ray Timing Explorer (RXTE) observations, we investigated the energy spectrum properties of the GX 339‐4 outburst in 2004 and confirmed that the outburst in 2004 is a mini‐outburst. It is very interest that the mini‐outburst has been through a whole state transition from Low/Hard state to High/Soft state. We also give a comparison between the normal outburst in 2002 and the mini‐outburst in 2004. And we find that the two outburst present a similar Hardness‐Intensity diagram and spectral properties, which suggest that the normal outburst and mini‐outburst have a similar physics. We think that the mini‐outburst of GX 339‐4 in 2004 can be well explained by the disk instability model. [ABSTRACT FROM AUTHOR]

Neural entity-linking models excel at bridging the lexical gap of multiple facets of facts, such as entity-related claims or evidence documents. Despite advancements in self-supervised learning and pretrained language models, challenges persist in entity linking, particularly in interpretability and transferability. Moreover, these models need many aligned documents to adapt to emerging entities, which may not be available due to data scarcity. In this work, we propose a novel Demonstrative Self-TrAining fRamework (D-STAR) that leverages multi-perspective thought navigation. D-STAR iteratively optimizes a question generator and an entity retriever by navigating thoughts on a dynamic graph reasoning across multiple perspectives for question generation. The generated question–answer pairs, along with hard negatives shared in the graph, enable adaptation with minimal computational overhead. Additionally, we introduce a new task, source-free entity linking, focusing on unsupervised transfer learning without direct access to original domain data. To demonstrate the feasibility of this task, we provide a generated question–answering dataset, FandomWiki , for novel entities. Our experiments show that D-STAR significantly improves baselines on SciFact, Zeshel, and FandomWiki. • Adapting a pretrained entity linking model for entity queries of emerging domains. • Dynamically prompting a large language model with multiperspective thought navigation algorithm. • Harnessing topological data to mine hard negatives in contrastive learning. • Conceptualizing source-free entity linking. [ABSTRACT FROM AUTHOR]

In response to the personalized needs of the tourism industry, intelligent tourism planning services should be adopted. Through artificial intelligence and Big data technology, users' travel preferences, time, budget and other information are analyzed and mined in depth to provide users with more suitable travel routes and services. Therefore, according to the demand of tourist path recommendation in cultural scenic spots, this paper proposes a light sensor positioning method based on deep learning algorithm. This paper expounds the advantages of using optical sensor positioning for path recommendation, and describes the specific steps and processes of the optical sensor positioning method based on deep learning algorithm in detail. Finally, the feasibility and effect of this method are verified by experiments and data analysis. The results show that the localization of light sensor based on deep learning algorithm has high accuracy and practicability in the travel path recommendation of cultural scenic spots. Therefore, this method can provide accurate and reasonable path recommendation for tourists in cultural scenic spots and improve tourism experience and benefits. With the continuous development of the tourism market and the changing needs of users, this personalized tourism route planning and recommendation system will be increasingly widely applied and promoted. [ABSTRACT FROM AUTHOR]

Currently, many types of non-linear topological structure polymers, such as brush-shaped, star, branched and dendritic structures, have captured much attention in the field of gene delivery and nanomedicine. Compared with linear polymers, non-linear topological structural polymers offer many advantages, including multiple terminal groups, broad and complicated spatial architecture and multi-functionality sites to enhance gene delivery efficiency and targeting capabilities. Nevertheless, the complexity of their synthesis process severely hampers the development and applications of nonlinear topological polymers. This review aims to highlight various synthetic approaches of non-linear topological architecture polymers, including reversible-deactivation radical polymerization (RDRP) including atom-transfer radical polymerization (ATRP), nitroxide-mediated polymerization (NMP), reversible addition-fragmentation chain transfer (RAFT) polymerization, click chemistry reactions and Michael addition, and thoroughly discuss their advantages and disadvantages, as well as analyze their further application potential. Finally, we comprehensively discuss and summarize different non-linear topological structure polymers for genetic materials delivering performance both in vitro and in vivo, which indicated that topological effects and nonlinear topologies play a crucial role in enhancing the transfection performance of polymeric vectors. This review offered a promising guideline for the design and development of novel nonlinear polymers and facilitated the development of a new generation of polymer-based gene vectors. [ABSTRACT FROM AUTHOR]

The transient wind is one of the dangerous conditions encountered by tethered UAVs operating at the ocean, making the cable and the UAV generate complex nonlinear vibration responses threatening normal operation, even safe flight. There is a lack of research on the nonlinear vibration of the tethered UAV in a transient wind field environment. This study analyzes the vibration response of a tethered quadrotor UAV under a transient wind field, which helps to boost the tethered UAV applications, providing engineering suggestions to design these systems. Considering both cable and UAV motions, the coupled dynamic equations of the tethered UAV system are established based on the Hamilton principle. The variation law of the cable vibration amplitudes with wind field and position is analyzed through a one-minus-cosine gust profile to describe the transient wind field, which can evaluate the dynamic behavior of systems in the actual flight. Moreover, the positions of maximum vibration amplitude in tangential and normal directions are found to be approximately 9/10 and 9/20 from the lower end of the cable. Furthermore, the tethered UAV system vibrations are investigated under different structural parameters. The results indicate that the UAV can maintain a stable single-period motion by increasing the length or elastic modulus or selecting the appropriate diameters of the cable. Finally, an experiment is implemented on the vibration response of the tethered UAV system in a wind tunnel. The theoretical result is compatible with the experimental one, demonstrating the theoretical method's accuracy. [ABSTRACT FROM AUTHOR]

This study aims to investigate the initial transient effects and the final steady-state sloshing characteristics under long-duration surge excitations experimentally. Liquids with different viscosity are applied in the sloshing experiments. The image recognition method is innovatively employed to accurately capture the free surface elevation in these experiments. The viscous effects are found to play a crucial role in altering the damping of the transient mode associated with its natural frequencies and the establishment of the steady-state mode related to the excitation frequency. The mechanism of viscous effects on energy dissipation and transferring is further revealed by Fast Fourier transform and wavelet transform. Then, the damping rates of liquid sloshing with different viscosities are quantitatively measured and analyzed, with reference to the early theories. It is found that with the use of the damping coefficient derived from the experimental data, we are able to describe the long-term evolution of sloshing using the potential flow theory corrected by a damping term, representing the viscous effects of a particular viscous liquid. The accuracy and applicability of this approach is further discussed in this paper. [ABSTRACT FROM AUTHOR]

Anomaly detection for multivariate time series has been widely used in industry and has become one of the hot research problems in the field of data mining. However, the existing anomaly detection methods still have the following limitations: (1) The topological relationship between sensors is complex and nonlinear, and it is difficult to effectively model the inter-sensor dependencies. (2) Most anomaly detection models tend to ignore the critical temporal information in different time steps when capturing the temporal dependencies. To address these problems, we propose a hybrid graph transformer network for multivariate time series anomaly detection (HGTMAD), which combines the transformer with graph convolution to predict multivariate time series-based anomalies. In the time domain, we design a new sparse metric transformer network to capture the time dependence, where the Wasserstein distance is used to measure out significant dot product pairs to learn a better time series representation. In the spatial domain, we design a new channel convolution transformer network fused with a graph convolution network to learn accurately the complex dependencies of multivariate time series in spatial and on feature dimensions based on a combination of local and global approaches. Extensive experiments on publicly available datasets further demonstrate that the proposed HGTMAD significantly outperforms the mainstream state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Representation transfer is a widely used technique in natural language processing. We propose methods of cleaning the dominant dataset of text simplification (TS) WikiLarge in multi-views to remove errors that impact model training and fine-tuning. The results show that our method can effectively refine the dataset. We propose to take the pre-trained text representations from a similar task (e.g., text summarization) to text simplification to conduct a continue-fine-tuning strategy to improve the performance of pre-trained models on TS. This approach will speed up the training and make the model convergence easier. Besides, we also propose a new decoding strategy for simple text generation. It is able to generate simpler and more comprehensible text with controllable lexical simplicity. The experimental results show that our method can achieve good performance on many evaluation metrics. • Using sentence representations to refine the dataset. • Fine-tuning by taking text representations from similar tasks. • A new decoding strategy for simple text generation. [ABSTRACT FROM AUTHOR]

Histamine (HIS) is primarily formed from decarboxylated histidine by certain bacteria with histidine decarboxylase (hdc) activity and is the most toxic biogenic amine. Hdc, which is encoded by the hdc gene, serves as a key enzyme that controls HIS production in bacteria. In this paper, we characterized the changes in microbial and biogenic amines content of traditional Sichuan‐style sausage before and after storage and demonstrated that Enterobacteriaceae play an important role in the formation of HIS. To screen for Enterobacteriaceae with high levels of HIS production, we isolated strain RH3 which has a HIS production of 2.27 mg/mL from sausages stored at 37°C for 180 days, using selective media and high‐performance liquid chromatography. The strain RH3 can produce a high level of HIS after 28 h of fermentation with a significant hysteresis. Analysis of the physicochemical factors revealed that RH3 still retained its ability to partially produce HIS in extreme environments with pH 3.5 and 10.0. In addition, RH3 exhibited excellent salt tolerance (6.0% NaCl and 1.0% NaNO2). Subsequently, RH3 was confirmed as Enterobacter hormaechei with hdc gene deletion by PCR, western blot, and whole‐genome sequencing analysis. Furthermore, RH3 exhibited pathogenicity rate of 75.60% toward the organism, indicating that it was not a food‐grade safe strain, and demonstrated a high level of conservation in intraspecific evolution. The results of this experiment provide a new reference for studying the mechanism of HIS formation in microorganisms. Practical Application: This study provides a new direction for investigating the mechanism of histamine (HIS) formation by microorganisms and provides new insights for further controlling HIS levels in meat products. Further research can control the key enzymes that form HIS to control HIS levels in food. [ABSTRACT FROM AUTHOR]

Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that affects individuals across their lifespan. Early diagnosis and intervention are crucial for improving outcomes. However, current diagnostic methods are often time-consuming, and costly, making them inaccessible to many families. In the current study, we aim to test caregiver-child interaction as a potential tool for screening children with ASD in clinic. Methods: We enrolled 85 preschool children (Mean age: 4.90 ± 0.65 years, 70.6% male), including ASD children with or without developmental delay (DD), and typical development (TD) children, along with their caregivers. ASD core symptoms were evaluated by Childhood Autism Rating Scale (CARS) and Autism Diagnostic Observation Schedule-Calibrated Severity Scores (ADOS-CSS). Behavioral indicators were derived from video encoding of caregiver-child interaction, including social involvement of children (SIC), interaction time (IT), response of children to social cues (RSC), time for caregiver initiated social interactions (GIS) and time for children initiated social interactions (CIS)). Power spectral density (PSD) values were calculated by EEG signals simultaneously recorded. Partial Pearson correlation analysis was used in both ASD groups to investigate the correlation among behavioral indicators scores and ASD symptom severity and PSD values. Receiver operating characteristic (ROC) analysis was used to describe the discrimination accuracy of behavioral indicators. Results: Compared to TD group, both ASD groups demonstrated significant lower scores of SIC, IT, RSC, CIS (all p values < 0.05), and significant higher time for GIS (all p values < 0.01). SIC scores negatively correlated with CARS (p = 0.006) and ADOS-CSS (p = 0.023) in the ASD with DD group. Compared to TD group, PSD values elevated in ASD groups (all p values < 0.05), and was associated with SIC (theta band: p = 0.005; alpha band: p = 0.003) but not IQ levels. SIC was effective in identifying both ASD groups (sensitivity/specificity: ASD children with DD, 76.5%/66.7%; ASD children without DD, 82.6%/82.2%). Conclusion: Our results verified the behavioral paradigm of caregiver-child interaction as an efficient tool for early ASD screening. [ABSTRACT FROM AUTHOR]

Remote sensing images are frequently contaminated by clouds that often degrade the performance of subsequent applications. Cloud removal, therefore, is a standard step in remote sensing image preprocessing, and single-image-based thin cloud removal is a well-established area of research. Existing single-image-based thin cloud removal methods however, lack the capacity for simultaneous executions of efficient long-range modeling and physical attribute consideration. To extend this work and fill this gap, a novel blind single-image-based thin cloud removal method, called cloud perception integrated fast Fourier convolutional network (CP-FFCN), was designed and implemented. The CP-FFCN consists of two modules: the cloud perception module (CPM) and a fast Fourier convolution (FFC)-conducted reconstruction module (FFCN). The CPM uses a frequency spatial attention mechanism to realize long-range modeling of clouds, globally detect them in the cloudy image. It helps the CP-FFCN remove the clouds without external prior knowledge of the cloud distribution. The reconstruction module was designed with an FFC-conducted U-Net architecture to recover the clean images from cloudy scenarios, guided by the locations of clouds as detected by the CPM. In addition, the FFC blocks deployed in the encoder and decoder components in the U-Net architecture selectively learn the attributes of clouds and fogs from the frequency spectrograms to remove the clouds and reconstruct the underlying ground objects. The CP-FFCN selectively learns the frequency features for adequate cloud separation and at the same time efficiently models the long-range information for comprehensive scenario reconstruction with the help of these two modules. We adopted the Google Earth data and Landsat-8 imagery to train the CP-FFCN model and evaluate it on simulated and naturally occurring cloudy scenarios. The visual outcomes illustrate that the proposed CP-FFCN successfully removes thin and small-scale thick clouds with complex ground object scenarios, without external cloud masks and additional reference data. The quantitative analyses further demonstrate the higher effectiveness of the CP-FFCN when compared with several other state-of-the-art thin cloud removal methods, yielding a PSNR value over 39.24 and a SSIM value over 0.98 on the Landsat 8 images. [ABSTRACT FROM AUTHOR]

Introduction: Currently, there exists considerable debate surrounding the optimal treatment approaches for different subtypes of patients with spinal cord injury (SCI). The purpose of this study was to conduct a comparative analysis of the benefits associated with conservative treatment and treatments with different surgical periods for patients diagnosed with acute traumatic central cord syndrome (ATCCS) and multilevel cervical canal stenosis (CCS). Methods: A retrospective cohort study was conducted, and 93 patients who met inclusion and exclusion criteria in our hospital between 2015 and 2020 were followed for a minimum duration of 2 years. Among them, 30 patients (Group A) received conservative treatment, 18 patients (Group B) received early surgery (≤7 days), and 45 patients (Group C) received late surgery (>7 days). The American Spinal Injury Association (ASIA) grade, Japanese Orthopedic Association (JOA) score, and recovery rate (RR) were evaluated. Multivariate linear regression was used to analyze prognostic determinants. Cost‐utility analysis was performed based on the EQ‐5D scale. Results: The ASIA grade, JOA score, and RR of all three groups improved compared with the previous evaluation (P < 0.05). During follow‐up, the ASIA grade, JOA score, and RR of Group B were all better than for Group A and Group C (P < 0.05), while there was no significant difference between Group A and C (P > 0.05). The EQ‐5D scale in Group B was optimal at the last follow‐up. The incremental cost‐utility ratio (ICUR) of Group A was the lowest, while that of Group B compared to Group A was less than the threshold of patients' willingness to pay. Age, initial ASIA grade, and treatment types significantly affected the outcomes. Conclusions: Both conservative and surgical treatments yield good results. Compared with patients who received conservative treatment and late surgery, patients who received early surgery had better clinical function and living quality. Despite the higher cost, early surgery is cost‐effective when compared to conservative treatment. Younger age, initial better ASIA grade, and earlier surgery were associated with better prognosis. [ABSTRACT FROM AUTHOR]

A soft and tunable microwave bandpass Chebyshev microstrip end-coupled filter is demonstrated on a polydimethylsiloxane substrate based on high electrically conductive composites made of silver nanoparticle-covered flakes, even with large strain. To achieve a precise design, key microwave parameters such as the impedance, S-parameters, and transmission matrix are defined as a function of strain. This strain vector polar coordinate is used to represent the relationship between the type and the performance of a filter. Then, the most important Chebyshev or quasi-Chebyshev type of filter can be accurately realized by looking up its polar coordinates to find the corresponding strain magnitude and direction of stretching. An end-coupled Chebyshev microstrip bandpass filter with a center frequency of 12.8 GHz and bandwidth of 22% was designed and fabricated for demonstration. Experimentally, at a lateral elongation of 8% and 10.7%, the center frequency decreases by 0.61 and 0.88 dB, respectively, matching the simulation results very well. One potential application for this tunable filter is a front-end module mounted on the biomimetic robot driven by its mechanic movements. [ABSTRACT FROM AUTHOR]

One-shot object detection has been a highly demanded yet challenging task since the early age of convolutional neural networks (CNNs). For some newly started projects, a handy network that can learn the target's pattern using a single picture and automatically decide its architecture is needed. To specifically address a scenario in which a single or multiple targets are standing in relatively stable circumstances with hardly any training data, where the rough location of the target is required, we propose a one-shot simple target detection model that focuses on two main tasks: (1) deciding if the target is in the testing image, and (2) if yes, outputting the target's location in the image. This model requires no pre-training and decides its architecture automatically; therefore, it could be applied to a newly started target detection project with unconventionally simple targets and few training examples. We also propose an architecture with a non-training parameter-gaining strategy and correlation coefficient-based feedforward and activation functions, as well as easy interpretability, which might provide a perspective on studies in neural networks. We tested this design on the data we collected in our project, the Brown–Yosemite dataset and part of the Mnist dataset. It successfully returned the target area in our project and obtained an IOU of up to 87.04%, reached 80.28% accuracy on the Brown–Yosemite dataset with disposable networks, and obtained an accuracy of up to 89.4% on part of the Mnist dataset in the detection task. [ABSTRACT FROM AUTHOR]

Brief interventions increase access to and engagement with care for people who are discharged presentation to emergency departments or inpatient care due to suicidal behavior. This study was to investigate the effectiveness of the Allied Health Brief Therapies (AHBT) clinic interventions on suicide ideation, health service utilization, negative emotional states, and functioning and well-being in consumers in suicidal crisis. This research was designed as pre-post study. Three AHBT clinics were established to provide brief interventions in Queensland Australia. Repeated measures ANOVA and McNemar's test were used to measure the impact of the interventions. Sensitivity analysis was conducted to ensure the robustness and appropriate interpretation of the results. Among the 141 consumers who accepted the referral, 106 (75.2%) attended the AHBT sessions, and 35 (24.8%) did not start the interventions. The AHBT clinic interventions reduced consumers' presence and frequency of suicide ideation, emergency department presentations, and negative emotional states (depression, anxiety, and stress), and increased their functioning and well-being with large effect sizes. Change in the frequency of inpatient admission after the AHBT clinic interventions was statistically non-significant. This study provides evidence that the AHBT clinics can reduce suicidal risk factors, decrease health service utilization, and increase functioning and well-being in consumers in suicidal crisis. Future research should consider the use of a control group to increase confidence in the findings. [ABSTRACT FROM AUTHOR]

As an important agricultural facility that supports efficient crop production and precise water management, center-pivot irrigated cropland (CPIC) plays a critical role in increasing crop yield and ensuring food security globally. Since the 1980s, CPIC has expanded significantly and has become one of the most valuable irrigated croplands in Brazil. However, national-scale and long-term CPIC products are currently unavailable, making spatiotemporal analysis for related ecological and economic factors challenging. In this study, we proposed a novel framework combining cloud platforms and deep learning algorithms to produce annual CPIC maps (ACMs) with 30 m spatial resolution in Brazil from 1985 to 2021. Leveraging all available Landsat-5, 7, and 8 images in Brazil, we generated three-band annual composite images to obtain stable image features for CPIC and alleviate the heterogeneity of CPIC. Then we constructed a large-scale training dataset covering different climatic zones of Brazil and spanning multiple years. Based on this dataset a CNN model was trained and applied to the whole of Brazil and generalized to other years. We deployed the CNN model to the cloud platform and combined it with Google Earth Engine to produce Brazil's annual CPIC Maps (ACMs). Moreover, we analyzed the spatiotemporal dynamics of CPIC and explored the impact of CPIC expansion on forests. The accuracy assessment demonstrated that our ACMs reached an average mIoU of 0.947 ± 0.021 for all study years, and the estimated CPIC area was highly consistent with official statistics. Our results indicated that Brazilian CPICs reached 1.8 × 106 ha in 2021, which was 45 times more than that in 1985. CPIC expansion occurred mainly in the states of Minas Gerais, Goiás, and Bahia over the past few decades, with an average annual increase in area of over 8,000 ha. We also found that CPIC expansion had encroached on 42,000 ha of shrubs and 25,000 ha of forests since 1985, and the impact was continuing and intensifying. To the best of our knowledge, the produced ACMs are the longest and most spatially detailed CPIC products in Brazil that reflect the CPIC spatiotemporal changes in the last four decades and can provide essential information services for Brazil's water resource management and agricultural decision-making. [ABSTRACT FROM AUTHOR]

Multi-modality three-dimensional (3D) object detection is a crucial technology for the safe and effective operation of environment perception systems in autonomous driving. In this study, we propose a method called context clustering-based radar and camera fusion for 3D object detection (ConCs-Fusion) that combines radar and camera sensors at the intermediate fusion level to achieve 3D object detection. We extract features from heterogeneous sensors and input them as feature point sets into the fusion module. Within the fusion module, we utilize context cluster blocks to learn multi-scale features of radar point clouds and images, followed by upsampling and fusion of the feature maps. Then, we leverage a multi-layer perceptron to nonlinearly represent the fused features, reducing the feature dimensionality to improve model inference speed. Within the context cluster block, we aggregate feature points of the same object from different sensors into one cluster based on their similarity. All feature points within the same cluster are then fused into a radar–camera feature fusion point, which is self-adaptively reassigned to the originally extracted feature points from a simplex sensor. Compared to previous methods that only utilize radar as an auxiliary sensor to camera, or vice versa, the ConCs-Fusion method achieves a bidirectional cross-modal fusion between radar and camera. Finally, our extensive experiments on the nuScenes dataset demonstrate that ConCs-Fusion outperforms other methods in terms of 3D object detection performance. [ABSTRACT FROM AUTHOR]