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Temperature-insensitive elastic modulus known as Elinvar effect is typically achievable in metastable titanium alloys only through thermomechanical processing. Here reports that a directly additively manufactured TiNb-based alloy exhibits Elinvar effect over a wide temperature range of 273 K. This is attributed to its α″+β dual-phase microstructure wherein both the elastic modulus and transition strain of the α″ phase increase monotonically with increasing temperature. The α″ phase was obtained by setting a base-plate temperature of 723 K to act as in-situ aging. This provides a new way to optimize mechanical and functional properties simultaneously by utilizing thermal fields of additive manufacturing.

The structure changes and hydrogen permeation behavior of Titanium alloy TA17 in simulated water environment of small modular reactor (SMR) at 320 °C for 8000h was investigated. We found a corrosion layer consist of TiO2 and FeTiO3 with a good hydrogen permeation resistance. The structure and hydrogen permeation resistance change with the increase of corrosion period. At the first corrosion period of 3000h, FeTiO3 grows rapidly with an exponential parameter of 0.663 fitted by parabolic law. As the initial TiO2 layer destroyed, the deuterium permeation flux increases. After the thickness of FeTiO3 reaches a limit at corrosion time of 4000h, there exists a dynamic balance between the growth and the dissolution of FeTiO3, result in a small fluctuant deuterium permeation flux at corrosion periods of 5000–8000h. The deuterium permeation flux of the corrosion layer can be two orders of magnitude lower to that of Titanium alloy TA17 substrate. The formation process of corrosion layer and its effect on hydrogen permeation resistance are discussed in detail.

Abstract Esophageal cancer (EC) poses a substantial threat to human health. The development of radioresistance in esophageal cancer cells is a critical factor contributing to local treatment failure and an unfavorable prognosis in affected patients. A comprehensive analysis was performed using bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) data from esophageal squamous cell carcinoma (ESCC) samples. Radioresistant ESCC cell lines were generated to explore the functional role of CCNG1. Various techniques, including gene knockdown, flow cytometry, and apoptosis assays, were utilized to evaluate alterations in radiosensitivity, cell cycle progression, and cell survival in response to CCNG1 modulation. Elevated CCNG1 expression was associated with poor clinical outcomes in ESCC patients and contributed to various malignant phenotypes in ESCC cells. In radioresistant ESCC cell lines, CCNG1 knockdown markedly increased radiosensitivity, as demonstrated by enhanced G2/M phase arrest and apoptosis following radiation exposure. CellChat analysis indicated a correlation between CCNG1 and the Wnt/β-catenin signaling pathway, while western blot (WB) analysis confirmed that CCNG1 functions as a downstream effector of Wnt/β-catenin. Our study has identified CCNG1 as a key regulator of radiosensitivity in ESCC, mediated through its interaction with the Wnt/β-catenin signaling pathway. Targeting the Wnt/β-catenin/CCNG1 axis presents a promising therapeutic strategy to enhance the efficacy of radiotherapy in ESCC, potentially overcoming radioresistance and improving patient outcomes.

Abstract Non-radiative recombination of perovskite solar cells (PSCs) will increase as a result of the numerous crystallographic defects that the solution-grown perovskite films will cause, particularly at the grain boundary and film surface. As a result, it negatively influences the performance of the device. Consequently, lowering perovskite film defects is a useful strategy for raising the efficiency of PSCs. This study reports a grain regeneration and passivation approach that can decrease the recombination loss of the perovskite layer/charge transfer layer interface and the grain border. Guanidine iodide (GAI) treatment of perovskite films is the means by which this objective is accomplished. Unlike most methods that use GAI to post-treatment the perovskite layer or add GAI into the perovskite precursor solution, this work uses GAI for pre-treatment before spin coating the perovskite layer. It can effectively passivate surface defects and increase the grain size of perovskite films by controlling the crystallization process. The water stability of devices was enhanced, the short-circuit current (J sc), filling factor (FF), and power conversion efficiency (PCE) of PSCs were markedly improved, and non-radiative recombination was successfully reduced. The best efficiency of PSCs was 20.56% after the additional GAI treatment was applied to the perovskite layer, an 11.9% increase over the efficiency of the control device without GAI treatment. This method has the advantage of being simple and straightforward, providing a feasible pathway for the low-cost preparation and commercialization of PSCs.

Currently, little is known about the characteristics of oxide films on Ti alloys exposed to the secondary circuit water environment of small modular reactors (SMRs). In this study, multiple microstructural characterization techniques were employed to meticulously characterize the oxide film characteristics of the TA16 alloy after 6000 h and 8000 h of exposure to a simulated SMR secondary circuit water environment. The results indicate that the oxide films on the 6000 h specimen are composed of a microcrystalline anatase TiO2 interior layer and a coarse-grained anatase TiO2 exterior layer, while the oxide film on the 8000 h specimen typically consists of a microcrystalline anatase TiO2 inner layer, an NiFe2O4 middle layer, and a coarse-grained anatase TiO2 outer layer. As the corrosion time is extended to 8000 h, the presence of NiFe2O4 oxide particles can be attributed to oxide deposition by the 316L stainless steel autoclave used in the corrosion experiments, which results in the migration of Ni and Fe ions onto the surface of the Ti alloy.

Abstract During the operation of load cell, heat is generated by the strain gauge and the electronics on the PCB board, which leads to temperature gradients within the sensor itself. These temperature gradients are unstable at different ambient temperatures. Compensation inaccuracies can also occur when compensating for sensor measurements at different temperatures This paper proposes a method to change the position of temperature compensation resistors to address errors caused by the temperature field effect of the strain gauge sensor itself. Without affecting the sensor’s strain measurement, the correctness of the proposed method is demonstrated through steady-state thermal simulation results in ANSYS and experimental results, effectively addressing errors caused by unstable temperature gradients during the operation of strain gauge sensors.

Abstract Objective This study aims to explore the association between the triglyceride-glucose (TyG) index and vitamin D status to enhance our understanding of how vitamin D status relates to metabolic health and to provide evidence for the early diagnosis of vitamin D deficiency (VDD) using the TyG index. Methods We conducted a comprehensive search in various databases, including PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biology Medicine disc, China Science and Technology Journal Database, and Wanfang Data to gather articles published from the inception of these databases until February 19, 2024. We assessed the quality of included studies using the Newcastle-Ottawa Scale (NOS) for case-control studies and the Agency for Healthcare Research and Quality (AHRQ) methodology checklist for cross-sectional studies. Statistical analyses in this study were conducted using conversion methods for non-standard data formats and consolidation techniques for combining multiple groups. The Fisher transformation method was used for correlation coefficients. We used a random-effects model considering the inherent clinical heterogeneity among the studies, and assessed statistical heterogeneity with the Cochrane Q test and I2 statistic, complemented by subgroup analyses and sensitivity analysis. Results Our meta-analysis selected a total of nine studies. The analysis revealed that patients with vitamin D deficiency (VDD group) exhibited a significantly higher TyG index than those without deficiency (no-VDD group), with a mean difference (MD) of 0.16 (95% CI: 0.10 to 0.23, I2 = 93%). This association was particularly pronounced among patients with type 2 diabetes (T2DM), showing an MD of 0.15 (95% CI: 0.05 to 0.26, I2 = 55%). Additionally, a negative correlation was observed between the TyG index and vitamin D levels, with a correlation coefficient (r) of -0.236 (95% CI: -0.310 to -0.159, I2 = 91%). Excluding each study sequentially in the sensitivity analyses did not significantly alter the outcomes. Conclusions Our findings demonstrate a significant association between the TyG index and vitamin D status across diverse populations, including those with T2DM, subclinical hypothyroidism (SCH), and metabolic associated fatty liver disease (NAFLD). Our results reveal a notable disparity in the TyG index between vitamin D deficient and non-deficient groups, suggesting that vitamin D may play a critical role in metabolic health. These findings highlight the need for further research to explore the underlying mechanisms and clinical implications of vitamin D in the context of various metabolic disorders.

Abstract Post-transcriptional regulation mediated by RNA binding proteins is crucial for male germline development. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), an RNA binding protein, is specifically expressed in human and mouse male gonads and is involved in manifold biological processes and tumorigenesis. However, the function of IGF2BP1 in mammalian spermatogenesis remains poorly understood. Herein, we generated an Igf2bp1 conditional knockout mouse model using Nanos3-Cre. Germ cell deficiency of Igf2bp1 in mice caused spermatogenic defects in an age-dependent manner, resulting in decreased numbers of undifferentiated spermatogonia and increased germ cell apoptosis. Immunoprecipitation-mass spectrometry analysis revealed that ELAV-like RNA binding protein 1, a well-recognized mRNA stabilizer, interacted with IGF2BP1. Single cell RNA-sequencing showed distinct mRNA profiles in spermatogonia from conditional knockout versus wide type mice. Further research showed that IGF2BP1 plays a vital role in the modulation of spermatogenesis by regulating Lin28a mRNA, which is essential for clonal expansion of undifferentiated spermatogonia. Thus, our results highlight the crucial effects of IGF2BP1 on spermatogonia for the long-term maintenance of spermatogenesis.

Abstract Digital transformation (DX) has become an important strategy for the sustainable development of traditional manufacturers. However, the impact of DX on the environment is still inconclusive, and whether it is beneficial for manufacturers to reduce total carbon emissions remains to be examined. Therefore, based on the carbon cap-and-trade policy, this paper employs a game-theoretic model to study the DX strategies of duopolistic manufacturers and to explore the influence of low-carbon policy on these strategies. Additionally, we compare the total carbon emissions before and after DX implementation by manufacturers, discussing the environmental implications of DX. And we innovatively segment the market into two scenarios: one with a low digital technology level and the other with a high digital technology level. Our research demonstrates that the appropriate DX strategy can not only boost manufacturers’ profits but also enhance their ability to withstand external shocks. In the scenario with a high level of digital technology, manufacturers can achieve greater profits and are more likely to reduce total carbon emissions, resulting in a win-win situation. Sensitivity analysis reveals that an increase in carbon trading prices encourages manufacturers to ramp up their investments, ultimately driving comprehensive DX. This study not only provides decision-making guidance for the DX of manufacturers, but also provides a direction for the government to promote DX and achieve carbon neutralization.

Change detection is an important task in geospatial analysis that aims to identify noticeable variations in geographic elements between images captured at different periods. However, existing methods often overlook the distribution discrepancies across images caused by changes in imaging time. Meanwhile, the spectral and spatial features of hyperspectral images still have great potential for further development in extracting and detecting changes. To mitigate these challenges, we propose a novel approach called domain alignment dynamic spectral and spatial feature fusion (DADSSFF) for hyperspectral change detection. First, DADSSFF uses the main network to optimize the alignment of the mean (first-order statistics) and correlation (variance, second-order statistics) of the bitemporal images, coordinating features across both levels to alleviate the issue of inconsistent feature distribution. Second, the Kullback–Leibler divergence is employed to increase the interaction between the two auxiliary networks and the main network, enhancing the extraction of spectral and spatial attention features from bitemporal hyperspectral images. Finally, the cosine similarity is applied to measure the weights of the spectral and spatial features, enabling a dynamic evaluation of their importance. The effectiveness of DADSSFF is demonstrated by experimental results on three classical hyperspectral change detection datasets.

Abstract Microbial communities exhibit intricate interactions underpinned by metabolic dependencies. To elucidate these dependencies, we present a workflow utilizing random matrix theory on metagenome-assembled genomes to construct co-occurrence and metabolic complementarity networks. We apply this approach to a temperature gradient hot spring, unraveling the interplay between thermal stress and metabolic cooperation. Our analysis reveals an increase in the frequency of metabolic interactions with rising temperatures. Amino acids, coenzyme A derivatives, and carbohydrates emerge as key exchange metabolites, forming the foundation for syntrophic dependencies, in which commensalistic interactions take a greater proportion than mutualistic ones. These metabolic exchanges are most prevalent between phylogenetically distant species, especially archaea-bacteria collaborations, as a crucial adaptation to harsh environments. Furthermore, we identify a significant positive correlation between basal metabolite exchange and genome size disparity, potentially signifying a means for streamlined genomes to leverage cooperation with metabolically richer partners. This phenomenon is also confirmed by another composting system which has a similar wide range of temperature fluctuations. Our workflow provides a feasible way to decipher the metabolic complementarity mechanisms underlying microbial interactions, and our findings suggested environmental stress regulates the cooperative strategies of thermophiles, while these dependencies have been potentially hardwired into their genomes during co-evolutions.

Abstract Objective To investigate the role of Parkin overexpression-induecd mitophagy in alleviating acute lung injury of exertional heat stroke(EHS) rats. Methods Eighty SD rats were divided into four groups: Control group (CON group), Control Parkin overexpression group (CON + Parkin group), exertional heat stroke group (EHS group), and exertional heat stroke Parkin overexpression group (EHS + Parkin group). Adeno-associated virus carrying the Parkin gene was intravenously injected into the rats to overexpress Parkin in the lung tissue. An exertional heat stroke rat model was established, and survival curves were plotted. Lung Micro-CT was performed, and lung coefficient and pulmonary microvascular permeability were measured. Enzyme-linked immunosorbent assays(ELISA) were used to determine the levels of interleukin-6(IL-6), interleukin-1β(IL-1β), Tumor necrosis factor-α(TNF-α), and reactive oxygen species(ROS). The morphology of mitochondria in type II epithelial cells of lung tissue was observed using transmission electron microscopy. The apoptosis of lung tissue, the level of mitophagy, and the co-localization of Pink1 and Parkin were determined using immunofluorescence. The expression of Pink1, Parkin, MFN2, PTEN-L, PTEN, p62, and microtubule associated protein 1 light chain 3 (LC3) in rat lung tissue was measured by western blot. Results Compared with the CON group, there were more severe lung injury and more higher levels of IL-6, IL-1β, TNF-α in EHS rats. Both of the LC3-II/LC3-I ratio and the co-localization of LC3 and Tom20 in the lung tissue of EHS rats decreased. Compared with the EHS group, the survival rate of rats in the EHS + Parkin overexpression group was significantly increased, lung coefficient and pulmonary microvascular permeability were reduced, and pathological changes such as exudation and consolidation were significantly alleviated. The levels of IL-6, IL-1β, TNF-α, and ROS were significantly decreased; the degree of mitochondrial swelling in type II alveolar epithelial cells was reduced, and no vacuolization was observed. Lung tissue apoptosis was reduced, and the colocalization fluorescence of Pink1 and Parkin, as well as LC3 and Tom20, were increased. The expression of Parkin and LC3-II/LC3-I ratio in lung tissue were both increased, while the expression of P62, Pink1, MFN2, and PTEN-L was decreased. Conclusion Pink1/Parkin-mediated mitophagy dysfunction is one of the mechanisms underlying acute lung injury in rats with EHS, and activation of Parkin overexpression induced-mitophagy can alleviate acute lung injury caused by EHS.

Abstract Background Hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis constitutes a pivotal response by surgical trauma, manifesting as a critical aspect of the acute stress reaction. This hyperactivity resulted in adverse surgical outcomes and is often associated with increased postoperative anxiety. Increased evidence suggests that Nesfatin-1 plays a crucial role in stress responses and stress-related psychiatric disorders. Electroacupuncture (EA) is widely used to alleviate stress responses and anxiety, although its mechanism of action remains unclear. This study aimed to assess the mechanisms by which hypothalamic Nesfatin-1 contribute to the alleviation of HPA axis hyperactivity and anxiety by EA. Methods Partial hepatectomy (HT) was performed to simulate surgical trauma, and EA was applied at Zusanli (ST36) and Sanyinjiao (SP6). The levels of hypothalamic Nesfatin-1, c-Fos, and corticotropin-releasing hormone (CRH) were detected, and serum adrenocorticotropic hormone (ACTH) and corticosterone (CORT) were regarded as indicators of HPA axis activity. Anxiety levels were assessed through open field tests (OFT), elevated plus maze (EPM), and light–dark box tests (LDBT). To investigate the role of Nesfatin-1, its expression was modulated using stereotactic viral injections or plasmid transfections. Transcriptome sequencing was employed to explore the downstream signaling pathways of Nesfatin-1. Additionally, brain cannula implantation was performed to facilitate targeted drug administration. Results Our findings demonstrated that EA reduced the hypothalamic overexpression of CRH and Nesfatin-1, as well as serum levels of ACTH and CORT. Additionally, it alleviated anxiety-like behaviors resulting from surgical trauma. We observed that overexpression of Nesfatin-1 in the hypothalamic paraventricular nucleus (PVN) triggered hyperactivity of the HPA axis and anxiety. Conversely, knocking down Nesfatin-1 in the PVN reversed these effects caused by surgical trauma. Transcriptome sequencing identified the extracellular regulated protein kinases (ERK)/cAMP-response element binding protein (CREB) pathway as a key mediator in the impacts of surgical trauma and EA on the hypothalamus. Both in vivo and in vitro studies showed that overexpression of Nesfatin-1 activated the ERK/CREB pathway. Furthermore, administering ERK or CREB inhibitors into the PVN mitigated HPA axis hyperactivity and anxiety-like behaviors induced by surgical trauma. Finally, EA was observed to decrease the phosphorylation levels of ERK and CREB in the PVN. Conclusion EA alleviates HPA axis hyperactivity and anxiety-like behaviors caused by surgical trauma through inhibition of Nesfatin-1/ERK/CREB pathway in the hypothalamus.

Selenium-enriched edible fungi are rich in selenium polysaccharides, selenoproteins, selenium polypeptides and other bioactive components. However, the selenium forms and organic selenium transformation rate of selenium-enriched edible fungi are affected by several factors, such as species, selenium biotransformation methods and cultivation techniques. Subsequently, edible fungi show different biological activities and mechanisms of action. Therefore, it is particularly important to study the forms, distribution, absorption and transformation of selenium in edible fungi. The paper reviews the proportion of different forms of selenium in total selenium, the process of absorption and transformation of different selenium forms, the threshold of total selenium, the present selenium-enriched technology and the industrial problems of representative selenium-enriched edible fungi. The immunological activity, antitumor activity and antioxidant activity of different selenium forms in selenium-enriched edible fungi are also discussed in this paper. This review is expected to provide a reference basis for the precise selenium enrichment of edible fungi, to serve as a scientific support for the development of highly active different forms of selenium, and to propose directions for the development of selenium-enriched edible fungi.

Abstract Background Extracellular matrix (ECM) stiffness is closely related to the progress of diabetic cardiomyopathy (DCM) and the response of treatment of DCM to anti-diabetic drugs. Dapagliflozin (Dapa) has been proven to have cardio-protective efficacy for diabetes and listed as the first-line drug to treat heart failure. But the regulatory relationship between ECM stiffness and treatment efficacy of Dapa remains elusive. Materials and methods This work investigated the effect of ECM stiffness on DCM progression and Dapa efficacy using both in vivo DCM rat model and in vitro myocardial cell model with high glucose injury. First, through DCM rat models with various levels of myocardial injury and administration with Dapa treatment for four weeks, the levels of myocardial injury, myocardial oxidative stress, expressions of AT1R (a mechanical signal protein) and the stiffness of myocardial tissues were obtained. Then for mimicking the stiffness of myocardial tissues at early and late stages of DCM, we constructed cell models through culturing H9c2 myocardial cells on the polyacrylamide gels with two stiffness and exposed to a high glucose level and without/with Dapa intervention. The cell viability, reactive oxygen species (ROS) levels and expressions of mechanical signal sensitive proteins were obtained. Results The DCM progression is accompanied by the increased myocardial tissue stiffness, which can synergistically exacerbate myocardial cell injury with high glucose. Dapa can improve the ECM stiffness-induced DCM progression and its efficacy on DCM is more pronounced on the soft ECM, which is related to the regulation pathway of AT1R-FAK-NOX2. Besides, Dapa can inhibit the expression of the ECM-induced integrin β1, but without significant impact on piezo 1. Conclusions Our study found the regulation and effect of biomechanics in the DCM progression and on the Dapa efficacy on DCM, providing the new insights for the DCM treatment. Additionally, our work showed the better clinical prognosis of DCM under early Dapa intervention.

Abstract Background This systematic study aims to assess the global epidemiologic, economic, and humanistic burden of illness associated with all types of hereditary angioedema. Methods A systematic search for articles reporting the epidemiologic, economic, and humanistic burden associated with patients with HAE was conducted using English and Chinese literature databases from the inception to May 23, 2022. The selected studies were assessed for their quality and risk of bias. The study was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses and registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022352377). Results In total, 65 articles that met the search inclusion criteria reported 10,310 patients with HAE, of whom 5861 were female patients. Altogether, 4312 patients (81%) and 479 patients (9%) had type 1 and type 2 HAE, respectively, whereas 422 patients (8%) had HAE-normal C1-INH. The overall prevalence of all types of HAE was between 0.13 and 1.6 cases per 100,000. The mean or median delay from the first onset of a symptom of HAE to confirmed diagnosis ranged from 3.9 to 26 years. The estimated risk of death from asphyxiation was 8.6% for patients with HAE. Hospitalization, medication, unnecessary surgeries, doctor visits, specialist services, and nursing costs are direct expenses that contribute to the growing economic burden. The indirect cost accounted mostly due to missing work ($3402/year) and loss of productivity ($5750/year). Furthermore, impairment of QoL as reported by patient-reported outcomes was observed. QoL measures identified depression, anxiety, and stress to be the most common symptoms for adult patients and children. Conclusion This study highlights the importance of early diagnosis and the need for improving awareness among health care professionals to reduce the burden of HAE on patients and society.

Abstract Rice sheath blight, caused by Rhizoctonia solani Kihn (R. solani), poses a significant threat to rice production and quality. Autotetraploid rice, developed through chromosome doubling of diploid rice, holds great potential for enhancing biological and yield traits. However, its resistance to sheath blight in the field has remained unclear. In this study, the field resistance of 35 autotetraploid genotypes and corresponding diploids was evaluated across three environments from 2020 to 2021. The booting stage was optimal for inoculating period based on the inoculation and analysis of R. solani at five rice growth stages. We found autotetraploids generally exhibited lower disease scores than diploids, indicating enhanced resistance after chromosome doubling. Among the 35 genotypes, 16 (45.71%) displayed increased resistance, 2 (5.71%) showed decreased resistance, and 17 (48.57%) displayed unstable resistance in different sowing dates. All combinations of the genotype, environment and ploidy, including the genotype-environment-ploidy interaction, contributed significantly to field resistance. Chromosome doubling increased sheath blight resistance in most genotypes, but was also dependent on the genotype-environment interaction. To elucidate the enhanced resistance mechanism, RNA-seq revealed autotetraploid recruited more down-regulated differentially expressed genes (DEGs), additionally, more resistance-related DEGs, were down-regulated at 24 h post inoculation in autotetraploid versus diploid. The ubiquinone/terpenoid quinone and diterpenoid biosynthesis pathways may play key roles in ploidy-specific resistance mechanisms. In summary, our findings shed light on the understanding of sheath blight resistance mechanisms in autotetraploid rice.

This paper concerns the invasion dynamics of the lattice pioneer-climax competition model with parameter regions in which the system is non-monotone. We estimate the spreading speeds and establish appropriate conditions under which the spreading speeds are linearly selected. Moreover, the existence of travelling waves is determined by constructing suitable upper and lower solutions. It shows that the spreading speed coincides with the minimum wave speed of travelling waves if the diffusion rate of the invasive species is larger or equal to that of the native species. Our results are new to estimate the spreading speed of non-monotone lattice pioneer-climax systems, and the techniques developed in this work can be used to study the invasion dynamics of the pioneer-climax system with interaction delays, which could extend the results in the literature. The analysis replies on the construction of auxiliary systems, upper and lower solutions, and the monotone dynamical system approach.

Three-dimensional (3D) geological models can visually present various underground geological body forms, geological structures, geological hazards, which is of great significance for urban spatial planning and urban geological hazard prevention and control. To overcome technical difficulties such as poor accuracy, poor aesthetics and the difficulty to modify and improve the model afterward, this paper proposes a 3D modeling technology for urban geology with multiple complex geological structures based on multi-source heterogeneous data with the common constraints of geological knowledge and geological laws. This technique can utilize various modeling data, such as DEM data, geological profiles, drillhole data, geophysical interpretation data and structure outline maps. Under the common constraints of geological prior knowledge and geological laws, the block modeling technique is used to complete the construction of 3D urban geological models under complex geological conditions. Taking the construction of 3D geological model in Chengdu as an example, this paper focuses on the theory and algorithm of 3D modeling of urban geology, the geological background of the demonstration area, the preparation and processing of 3D modeling data, and the research and demonstration application of 3D modeling technology for urban geology.

Within the context of the long-term development plan of batch loading of accident-tolerant fuel assemblies, an equivalent physical model of lead test assemblies is established based on the requirements of radiation testing and the applicability of analysis software. The quantitative assessment has been conducted on the impacts of parameters including zirconium alloy cladding coating and pellet additives on reactivity of fuel assembly. Concurrently, the fuel management strategy is optimized in alignment with the irradiation test objectives of ATF assemblies, leading to the creation of an evaluation process tailored for ATF assembly loading pattern. Focusing on the irradiation of the lead test assemblies into a nuclear power plant in China, three-cycle nuclear reactor loading pattern are designed, which are taking into account the economic, safety, and irradiation testing goals of the nuclear power plant. Simultaneously, the neutronic characteristics are also evaluated, quantitatively. The results show that the established equivalent physical model can effectively represent the characteristics of the lead test assemblies. The loading patterns designed based on the Optimised fuel management strategy achieve the desired goals in terms of economy, safety and radiation test requirements. The designed loading pattern evaluation process and equivalent model analysis method in this work provide guidance for the subsequent engineering design and application of irradiation testing for lead test assemblies.

Abstract With the increasing demand for multifunctional optoelectronic devices, flexible electrochromic energy storage devices are being widely recognized as promising platforms for diverse applications. However, simultaneously achieving high capacitance, fast color switching and large optical modulation range is very challenging. In this study, the MXene-based flexible in-plane microsupercapacitor was fabricated via a mask-assisted spray coating approach. By adding electrochromic ethyl viologen dibromide (EVB) into the electrolyte, the device showed a reversible color change during the charge/discharge process. Due to the high electronic conductivity of the MXene flakes and the fast response kinetics of EVB, the device exhibited a fast coloration/bleaching time of 2.6 s/2.5 s, a large optical contrast of 60%, and exceptional coloration efficiency. In addition, EVB acted as a redox additive to reinforce the energy storage performance; as a result, the working voltage window of the Ti3C2-based symmetric aqueous microsupercapacitor was extended to 1 V. Moreover, the device had a high areal capacitance of 12.5 mF cm−2 with superior flexibility and mechanical stability and showed almost 100% capacitance retention after 100 bending cycles. The as-prepared device has significant potential for a wide range of applications in flexible and wearable electronics, particularly in the fields of camouflage, anticounterfeiting, and displays.

Abstract Areca nut, the seed of Areca catechu L., is one of the most widely consumed addictive substances in the world after nicotine, ethanol, and caffeine. The major effective constituent of A. catechu, arecoline, has been reported to affect the central nervous system. Less is known if it may affect pain and its related emotional responses. In this study, we found that oral application of arecoline alleviated the inflammatory pain and its induced anxiolytic and anti-depressive-like behavior. Arecoline also increased the mechanical nociceptive threshold and alleviated depression-like behavior in naïve mice. In the anterior cingulate cortex (ACC), which acts as a hinge of nociception and its related anxiety and depression, by using the multi-electrode field potential recording and whole-cell patch-clamp recording, we found that the evoked postsynaptic transmission in the ACC of adult mice has been inhibited by the application of arecoline. The muscarinic receptor is the major receptor of the arecoline in the ACC. Our results suggest that arecoline alleviates pain, anxiety, and depression-like behavior in both physiological and pathological conditions, and this new mechanism may help to treat patients with chronic pain and its related anxiety and disorder in the future.

Abstract Objective Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario. Methods In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People’s Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People’s Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction. Results The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively. Conclusion The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Abstract Background Diabetic cardiomyopathy (DCM) poses a growing health threat, elevating heart failure risk in diabetic individuals. Understanding DCM is crucial, with fibroblasts and endothelial cells playing pivotal roles in driving myocardial fibrosis and contributing to cardiac dysfunction. Advances in Multimodal single-cell profiling, such as scRNA-seq and scATAC-seq, provide deeper insights into DCM’s unique cell states and molecular landscape for targeted therapeutic interventions. Methods Single-cell RNA and ATAC data from 10x Multiome libraries were processed using Cell Ranger ARC v2.0.1. Gene expression and ATAC data underwent Seurat and Signac filtration. Differential gene expression and accessible chromatin regions were identified. Transcription factor activity was estimated with chromVAR, and Cis-coaccessibility networks were calculated using Cicero. Coaccessibility connections were compared to the GeneHancer database. Gene Ontology analysis, biological process scoring, cell-cell communication analysis, and gene-motif correlation was performed to reveal intricate molecular changes. Immunofluorescent staining utilized various antibodies on paraffin-embedded tissues to verify the findings. Results This study integrated scRNA-seq and scATAC-seq data obtained from hearts of WT and DCM mice, elucidating molecular changes at the single-cell level throughout the diabetic cardiomyopathy progression. Robust and accurate clustering analysis of the integrated data revealed altered cell proportions, showcasing decreased endothelial cells and macrophages, coupled with increased fibroblasts and myocardial cells in the DCM group, indicating enhanced fibrosis and endothelial damage. Chromatin accessibility analysis unveiled unique patterns in cell types, with heightened transcriptional activity in myocardial cells. Subpopulation analysis highlighted distinct changes in cardiomyocytes and fibroblasts, emphasizing pathways related to fatty acid metabolism and cardiac contraction. Fibroblast-centered communication analysis identified interactions with endothelial cells, implicating VEGF receptors. Endothelial cell subpopulations exhibited altered gene expressions, emphasizing contraction and growth-related pathways. Candidate regulators, including Tcf21, Arnt, Stat5a, and Stat5b, were identified, suggesting their pivotal roles in DCM development. Immunofluorescence staining validated marker genes of cell subpopulations, confirming PDK4, PPARγ and Tpm1 as markers for metabolic pattern-altered cardiomyocytes, activated fibroblasts and endothelial cells with compromised proliferation. Conclusion Our integrated scRNA-seq and scATAC-seq analysis unveils intricate cell states and molecular alterations in diabetic cardiomyopathy. Identified cell type-specific changes, transcription factors, and marker genes offer valuable insights. The study sheds light on potential therapeutic targets for DCM.

Abstract Leveraging the ultra‐wideband advantages of the terahertz band, Integrated sensing and communication (ISAC) facilitates high‐precision sensing demands in human smart home applications. ISAC channel characteristics are the basis for ISAC system design. Currently, the ISAC channel is divided into target and background channels. Existing researches primarily focus on the attributes of human target itself, e.g. radar cross‐section and micro‐Doppler effect. However, the impact of human target on neither the pathloss characteristic of background channel nor the multipath propagation characteristic of target channel is considered. To address the gap, we conduct indoor channel measurements at 105 GHz to investigate the ISAC channel characteristics with the impact of human target. Firstly, by analysing the power angular delay profiles with and without human target, the changes in quantity and power of multipath components (MPCs) are observed. Then, a parameter called power control factor is proposed to evaluate the human target impact on pathloss, thereby modifying the existing pathloss model of background channel. Eventually, the MPCs belonging to target channel are extracted within target‐oriented power delay profile to count the power proportion of each bounce MPCs of the target‐Rx link, which supports the necessity of multi‐bounce (indirect) paths modelling in target channel.

AimsInflammatory diets can trigger chronic inflammation and affect gut microbiota. However, the relationship between dietary preferences and sensorineural hearing loss (SNHL) remains unclear. This study aims to elucidate the relationship between different dietary preferences and sensorineural deafness.MethodsThe Dietary Inflammation Index (DII) and SNHL were defined by data from the National Health and Nutrition Examination Survey (NHANES), and exploring their relationship. Using Mendelian randomization (MR) to analyze the relationship between 34 dietary preferences, 211 gut microbiota, and SNHL.ResultsSmooth curve fitting indicated that the risk of SNHL increased with increasing DII score when the DII score was greater than 5.15. MR results suggest that a diet including both oily and non-oily fish can substantially reduce the risk of SNHL. Additionally, six specific gut microbiota were found to have significant causal relationship with SNHL.ConclusionAn inflammatory diet may increase the risk of developing SNHL. The observed relationship between fish consumption, gut microbiota, and SNHL suggests the existence of a gut-inner ear axis.

Background Perioperative neurocognitive disorders (PND) refer to neurocognitive abnormalities during perioperative period, which are a great challenge for elderly patients and associated with increased morbidity and mortality. Our studies showed that long non-coding RNAs (lncRNAs) regulate mitochondrial function and aging-related pathologies in the aged hippocampus after anesthesia, and lncRNAs are associated with multiple neurodegenerations. However, the regulatory role of lncRNAs in PND-related pathological processes remains unclear. Methods A total of 18-month mice were assigned to control and surgery (PND) groups, mice in PND group received sevoflurane anesthesia and laparotomy. Cognitive function was assessed with fear conditioning test. Hippocampal RNAs were isolated for sequencing, lncRNA and microRNA libraries were constructed, mRNAs were identified, Gene Ontology (GO) analysis were performed, and lncRNA-microRNA-mRNA networks were established. qPCR was performed for gene expression verification. Results A total of 312 differentially expressed (DE) lncRNAs, 340 DE-Transcripts of Uncertain Coding Potential (TUCPs), and 2,003 DEmRNAs were identified in the hippocampus between groups. The lncRNA-microRNA-mRNA competing endogenous RNA (ceRNA) network was constructed with 29 DElncRNAs, 90 microRNAs, 493 DEmRNAs, 148 lncRNA-microRNA interaction pairs, 794 microRNA-mRNA interaction pairs, and 110 lncRNA-mRNA co-expression pairs. 795 GO terms were obtained. Based on the frequencies of involved pathological processes, BP terms were divided into eight categories: neurological system alternation, neuronal development, metabolism alternation, immunity and neuroinflammation, apoptosis and autophagy, cellular communication, molecular modification, and behavior changes. LncRNA-microRNA-mRNA ceRNA networks in these pathological categories were constructed, and involved pathways and targeted genes were revealed. The top relevant lncRNAs in these ceRNA networks included RP23-65G6.4, RP24-396L14.1, RP23-251I16.2, XLOC_113622, RP24-496E14.1, etc., and the top relevant mRNAs in these ceRNA networks included Dlg4 (synaptic function), Avp (lipophagy), Islr2 (synaptic function), Hcrt (regulation of awake behavior), Tnc (neurotransmitter uptake). Conclusion In summary, we have constructed the lncRNA-associated ceRNA network during PND development in mice, explored the role of lncRNAs in multiple pathological processes in the mouse hippocampus, and provided insights into the potential mechanisms and therapeutic gene targets for PND.

Abstract Primate‐specific DAZ (deleted in azoospermia) has evolved in the azoospermia factor c (AZFc) locus on the Y chromosome. Loss of DAZ is associated with azoospermia in patients with deletion of the AZFc region (AZFc_del). However, the molecular mechanisms of DAZ in spermatogenesis remain uncertain. In this study, the molecular mechanism of DAZ is identified, which is unknown since it is identified 40 years ago because of the lack of a suitable model. Using clinical samples and cell models, it is shown that DAZ plays an important role in spermatogenesis and that loss of DAZ is associated with defective proliferation of c‐KIT‐positive spermatogonia in patients with AZFc_del. Mechanistically, it is shown that knockdown of DAZ significantly downregulated global translation and subsequently decreased cell proliferation. Furthermore, DAZ interacted with PABPC1 via the DAZ repeat domain to regulate global translation. DAZ targeted mRNAs that are involved in cell proliferation and cell cycle phase transition. These findings indicate that DAZ is a master translational regulator and essential for the maintenance of spermatogonia. Loss of DAZ may result in defective proliferation of c‐KIT‐positive spermatogonia and spermatogenic failure.

Background: Surgical pain affects postoperative sleep quality, and they jointly form a vicious cycle of mutual influence. The cycle of postoperative pain and sleep disorders could lead to delirium, cardiovascular disease, and hyperalgesia, which significantly affect patients' postoperative recovery. Thus, exploring this phenomenon is of great importance for surgical patients, and warrants further investigation. Objective: By employing bibliometric methods, this study systematically analyzes the publications on postoperative pain-sleep disorders, identifies research trends and field dynamics, and ultimately provides insights for further progress in this research area. Methods: In this study, we searched the Web of Science database for studies on postoperative pain and sleep disorders from 2013 to 2023, and analyzed the number of publications, journals, authors, institutions, country regions, and keywords by utilizing CiteSpace, VOSviewer, and Bibliometrix. Results: The 1894 retrieved publications showed a trend of increasing number of publications and correlations between postoperative pain and sleep disorders from 2013 to 2023. The top countries for publications included the USA, China, etc., establishing a global collaborative network centered around the USA, China, and Europe. The top institutions for publications included University of California System, Harvard University, etc. The top authors include Christine Miaskowski, Steven M. Paul, Qiuling Shi, etc. These publications involved multiple disciplines including surgery, neurology, and anesthesiology, and various research funds including NIH, HHS, NSFC, etc. The top journals for publications included the European Archives of Oto-Rhino-Laryngology, etc. Keywords that appear most frequently in this field include ''pain'', ''surgery'', ''quality of life'', ''sleep'', ''depression'', and ''outcomes''. The thematic map indicated that the hot topics in this area include obstructive sleep apnea, tonsillectomy, children, pain, quality of life, and sleep. The undeveloped topics with research potential included postoperative pain, analgesia and dexmedetomidine, breast cancer, fatigue, and lung cancer. Conclusion: The increased number of publications and correlations between postoperative pain and sleep disorders, and the collaborative network across the USA, China, and Europe indicate a growing global interest in this area. This study also provides valuable insights into the trend of hot topics and frontiers and shows that this is an evolving and dynamic research area.

The nitrogen (N) cycle is the foundation of the biogeochemistry on Earth and plays a crucial role in global climate stability. It is one of the most important nutrient cycles in high-altitude lakes. The biogeochemistry of nitrogen is almost entirely dependent on redox reactions mediated by microorganisms. However, the nitrogen cycling of microbial communities in the high-altitude saline lakes of the Qinghai-Tibet Plateau (QTP), the world’s “third pole” has not been investigated extensively. In this study, we used a metagenomic approach to investigate the microbial communities in four high-altitude pristine saline lakes in the Altun mountain on the QTP. We observed that Proteobacteria, Bacteroidota, and Actinobacteriota were dominant in these lakes. We reconstructed 1,593 bacterial MAGs and 8 archaeal MAGs, 1,060 of which were found to contain nitrogen cycle related genes. Our analysis revealed that nitrite reduction, nitrogen fixation, and assimilatory nitrate reduction processes might be active in the lakes. Denitrification might be a major mechanism driving the potential nitrogen loss, while nitrification might be inactive. A wide variety of microorganisms in the lake, dominated by Proteobacteria, participate together in the nitrogen cycle. The prevalence of the dominant taxon Yoonia in these lakes may be attributed to its well-established nitrogen functions and the coupled proton dynamics. This study is the first to systematically investigate the structure and nitrogen function of the microbial community in the high-altitude pristine saline lakes in the Altun mountain on the QTP. As such, it contributes to a better comprehension of biogeochemistry of high-altitude saline lakes.

Abstract Cigarette smoke (CS) has been generally recognized as a chief carcinogenic factor in renal cell carcinoma (RCC). The stimulative effect of CS on renal cancer stem cells (RCSCs) has been described previously. The Sonic Hedgehog (SHH) pathway plays an essential role in self-renewal, cell growth, drug resistance, metastasis, and recurrence of cancer stem cells (CSCs). Renal cancer-related gene ΔNp63α is highly expressed in renal epithelial tissues and contributes to the RCSCs characteristics of tumors. The aim of this study was to elucidate the role of ΔNp63α and the SHH pathway on the activity of RCSCs induced by CS through a series of in vivo and in vitro studies. It was shown that in renal cancer tissues, ΔNp63α and RCSCs markers in smokers are expressed higher than that in non-smokers. RCSCs were effectively enriched by tumor sphere formation assay. Besides, CS increased the expression of RCSCs markers and the capability of sphere-forming in vitro and in vivo. Moreover, the SHH pathway was activated, and the specialized inhibitor alleviated the promotion of CS on RCSCs. ΔNp63α activated the SHH pathway and promoted CS-induced enhancement of RCSCs activity. These findings indicate that ΔNp63α positively regulates the activity of CS-induced RCSCs via the SHH pathway.

Abstract Background Eosinophilic gastritis (EoG) has rarely been reported in conjunction with gluten-sensitive enteropathy (GSE). When this does occur, patients typically present with gastrointestinal symptoms. To our knowledge, hypoproteinemia has not been reported as the primary manifestation. Anti-IgE therapy, such as omalizumab, lowers eosinophil counts in the blood, lungs, and gut. Its efficiency in treating active EoG remain unknown. Case presentation We report a 33-month-old boy with a history of food allergy and atopic dermatitis who developed recurrent edema, hypoproteinemia, and eosinophilia at the age of 14 months. The diagnoses of EoG and GSE were confirmed based on the clinical presentation and results of gastrointestinal biopsies and serological testing. Although prednisone and dietary intervention were initially effective, the boy developed prednisone-related facial swelling. After stopping prednisone, his symptoms relapsed. Subsequent treatment with omalizumab, combined with dietary intervention, showed good efficacy and safety. Conclusions To our knowledge, this is the first case of concurrent EoG and GSE that presented primarily with hypoproteinemia. We highlight the rare manifestations of these two diseases to raise clinical suspicion and prevent missed and delayed diagnoses. The pathogenesis of EoG is heterogeneous and complex. Omalizumab showed good efficacy, indicating that IgE-mediated processes may be involved in the pathogenesis of this patient’s diseases.

The electron-phonon (el-ph) and phonon-phonon interactions play a key role in determining electronic and thermal transport properties, respectively, in promising two-dimensional (2D) semiconductor devices. In this study, we investigated el-ph interactions using Wannier-Fourier interpolation method and renormalized phonon scattering considering finite-temperature effects in Bi2TeSe2 monolayer. The results show that the optical phonon modes dominate the carrier scattering, where level repulsion induced by crystal field splitting and spin-orbit coupling (SOC) effect effectively suppresses intervalley scattering, leading to high hole mobility. Moreover, the strong anharmonicity in Bi2TeSe2 monolayer results in the temperature-dependent softening of its optical phonons, along with a corresponding variation in interatomic force constants (IFCs). As a result, the lattice thermal conductivity is remarkably low and exhibits weak temperature dependence. Finally, the predicted dimensionless thermoelectric figure of merit exceeds unity in the range of 200–800 K, indicating the potential of Bi2TeSe2 monolayer for thermoelectric applications. This work provides new insights into the elimination of intervalley scattering by crystal field splitting and SOC effects, and paves the way for the evaluation of thermoelectric properties of materials with complex scattering mechanisms and strong anharmonicity.

The pervasive presence of mixed pixels in hyperspectral remote sensing imagery poses a substantial constraint on the quantitative progress of remote sensing technology. Hyperspectral unmixing (HU) techniques serve as effective means to address this issue. In recent years, deep learning methods, particularly autoencoders (AEs), have been progressively employed in blind HU due to their compatibility with linear mixture models. However, most of the current advanced AE unmixing networks are based on a single-stage framework that conducts the unmixing task solely from a spectral perspective. This makes the rich spatial information ignored and makes it difficult for the network to obtain discriminative compression features while being susceptible to spectral variability and noise outliers. To address these issues, we propose a new deep shared fully connected autoencoder (DSFC-AE) unmixing network. The proposed DSFC-AE network comprises dual branches that utilize distinct data inputs for feature extraction: the original spectral data and coarse-scale spectral data obtained through superpixel segmentation. Furthermore, shared weight strategies are applied to the corresponding dimension reduction layers of the encoder, facilitating effective feature fusion. In addition, we integrate two constraint terms into the loss function, harnessing the sparsity of abundances and the geometric features of endmembers. We evaluate the DSFC-AE method against three traditional methods and four state-of-the-art deep learning algorithms using multiple real datasets. The results unequivocally demonstrate that the proposed network achieves significant improvements in both accuracy and stability.

Most of current prostheses can offer motor function restoration for limb amputees but usually lack natural and intuitive sensory feedback. Many studies have demonstrated that Transcutaneous Electrical Nerve Stimulation (TENS) is promising in non-invasive sensation evoking for amputees. However, the objective evaluation and mechanism analysis on sensation feedback are still limited. This work utilized multi-channel TENS with diverse stimulus patterns to evoke sensations on four non-disabled subjects and two transradial amputees. Meanwhile, electroencephalogram (EEG) was collected to objectively assess the evoked sensations, where event-related potentials (ERPs), brain electrical activity maps (BEAMs), and functional connectivity (FC) were computed. The results show that various sensations could be successfully evoked for both amputees and non-disabled subjects by customizing stimulus parameters. The ERP confirmed the sensation and revealed the sensory-processing-related components like N100 and P200; the BEAMs confirmed the corresponding regions of somatosensory cortex were activated by stimulation; the FC indicated an increase of interactions between the regions of sensorimotor cortex. This study may shed light on how the brain responds to external stimulation as sensory feedback and serve as a pilot for further bidirectional closed-loop prosthetic control.

The improvement of fault diagnosis for complex equipment is an important step towards intelligent systems. Unlike component-level fault detection, system-level fault diagnosis presents new challenges, such as the integration of multiple sensors, the handling of massive datasets, and the necessity for robust system-level decision-making. To address these challenges, this paper proposes a novel Physics-embedded Recurrent Graph Neural Network (Pe-RGNN). By embedding physical knowledge about the interdependencies among sensors, the graph constructed of sensors are built through physical knowledge obtaining from high-fidelity model. With the sensory graph, the parameters are modeled through recurrent graph neural network to extract the temporal information. The proposed model has the advantage of simultaneously considering both spatial and temporal information. Experimental results from both simulated and real-world tests demonstrate the superior performance of the Pe-RGNN in early fault detection and fault identification accuracy when compared to traditional graph neural networks. These findings highlight the importance of incorporating both physical knowledge and time-series information in fault diagnosis models.

Radar error is a significant factor restricting the detection accuracy of radar. Improving the detection accuracy of radar is crucial to accurate target localization in an ocean environment. With a large amount of measured data, this paper presents the correlation analysis of radar errors, and gives the assumptions needed for radar error modeling. This provides theoretical support for calibrating the modeling method based on the radar error in the simultaneous observation of double targets. First, three error correction models were developed with constant, first-order, and second-order fitting methods, based on the origin and transfer of error in the radar system and the principles of error elimination and reduction in a cooperative platform. Subsequently, the advantages of using a cooperative platform including information sharing were used to detail the collection and preliminary processing of measured radar data as well as the establishment of datasets. Ultimately, the measured radar data were analyzed considering the random error of radar, the strategy for the selection of the optimal error correction model, and the detection error correlation of double targets. In particular, the second-order fitting model with the strongest azimuthal systematic error correlation calculated the root mean square error, which was 32.07% higher compared to the other two models. As revealed in the results of the error analysis, the random error of radar does not agree with the vector superposition characteristic, and it is strongly correlated with the system error of a single radar system that observes different targets within a short period. This provides a way for resolving some problems such as accurate target localization and time variance of error in the complex ocean environment.

Due to the extensive genetic and antigenic variation in Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), as well as its rapid mutability and evolution, PRRS prevention and control can be challenging. An expeditious and sensitive neutralization assay for PRRSV is presented to monitor neutralizing antibodies (NAbs) in serum during vaccine research. Here, a PRRSV expressing eGFP was successfully rescued with reverse genetics based on the infectious clone HuN4-F112-eGFP which we constructed. The fluorescent protein expressions of the reporter viruses remained stable for at least five passages. Based on this reporter virus, the neutralization assay can be easily used to evaluate the level of NAbs by counting cells with green fluorescence. Compared with the classical CPE assay, the newly developed assay increases sensitivity by one- to four-fold at the early antibody response stage, thus saving 2 days of assay waiting time. By using this assay to unveil the dynamics of neutralizing antibodies against PRRSV, priming immunity through either a single virulent challenge or only vaccination could produce limited NAbs, but re-infection with PRRSV would induce a faster and stronger NAb response. Overall, the novel HuN4-F112-eGFP-based neutralization assay holds the potential to provide a highly efficient platform for evaluating the next generation of PRRS vaccines.

Abstract Tannins as plant extracts have emerged as promising and potential alternatives for antibiotics in modern livestock cultivation systems. This study investigates the effect of dietary chestnut tannin extract (CTE) in finishing Tan lambs. Twenty-seven male Tan lambs were randomly divided into three groups: (1) control group (CON; basal diet); (2) low-dose CTE group (LCTE; basal diet + 2 g/kg CTE, dry matter [DM] basis); (3) high-dose CTE group (HCTE; basal diet + 4 g/kg CTE, DM basis). The HCTE group exhibited markedly higher average daily gain (ADG) and DM intake than CON (P

In the field of multimodal understanding and generation, tackling inherent uncertainties is essential for mitigating ambiguous interpretations across multiple targets. We introduce the Probability Distribution Encoder (PDE), a versatile, plug-and-play module that utilizes sequence-level and feature-level interactions to model these uncertainties as probabilistic distributions. Furthermore, we demonstrate its adaptability by seamlessly integrating PDE into established frameworks. Compared to previous methods, our probabilistic approach substantially enriches multimodal semantic understanding. In addition to specific tasks, the unlabeled data contains rich prior knowledge, especially multimodal uncertainties. However, current pre-training methods are designed based on point representations, which hinders the effective functioning of our distribution representations. Therefore, we incorporate this uncertainty modeling into three new pre-training strategies: Distribution-based Vision-Language Contrastive Learning (D-VLC), Distribution-based Masked Language Modeling (D-MLM), and Distribution-based Image-Text Matching (D-ITM). Empirical experiments show that our models achieve State-of-the-Art (SOTA) results in a range of downstream tasks, including image-text retrieval, visual question answering, visual reasoning, visual entailment and video captioning. Furthermore, the qualitative results reveal several superior properties conferred by our methods, such as improved semantic expressiveness over point representations, and the ability to generate diverse yet accurate predictions.

Hyperspectral change detection (CD) aims to obtain the change information of objects in the multitemporal hyperspectral images (HSIs). Recently, with the advantages in fully extracting the image features of irregular areas, the graph convolutional network (GCN) has attracted increasing attention for hyperspectral CD. The existing GCN-based CD methods usually use a graph structure constructed by superpixels to reduce the computational cost, which ignores the multiorder difference information among graph nodes and the local difference information within superpixels. To address these problems, this article proposes an efficient multiorder GCN with a channel attention module (CAM) for hyperspectral CD. Specifically, the multiorder GCN module is designed by repeatedly mixing the feature representations of neighborhoods. The CAM is then proposed to enhance the difference features of bitemporal HSIs. After that, the pixel-wise CD is accomplished by a lightweight feature fusion module and a fully connected layer. Experiments on three hyperspectral datasets illustrated the effectiveness of the proposed algorithm.

In crop breeding, genomic selection (GS) serves as a powerful tool for predicting unknown phenotypes by using genome-wide markers, aimed at enhancing genetic gain for quantitative traits. However, in practical applications of GS, predictions are not always made within populations or for individuals that are genetically similar to the training population. Therefore, exploring possibilities and effective strategies for across-population prediction becomes an attractive avenue for applying GS technology in breeding practices. In this study, we used an existing maize population of 5820 hybrids as the training population to predict another population of 523 maize hybrids using the GBLUP and BayesB models. We evaluated the impact of optimizing the training population based on the genetic relationship between the training and breeding populations on the accuracy of across-population predictions. The results showed that the prediction accuracy improved to some extent with varying training population sizes. However, the optimal size of the training population differed for various traits. Additionally, we proposed a population structure-based across-population genomic prediction (PSAPGP) strategy, which integrates population structure as a fixed effect in the GS models. Principal component analysis, clustering, and Q-matrix analysis were used to assess the population structure. Notably, when the Q-matrix was used, the across-population prediction exhibited the best performance, with improvements ranging from 8 to 11% for ear weight, ear grain weight and plant height. This is a promising strategy for reducing phenotyping costs and enhancing maize hybrid breeding efficiency.

The use of light energy to drive asymmetric organic transformations to produce high-value-added organic compounds is attracting increasing interest as a sustainable strategy for solving environmental problems and addressing the energy crisis. Chiral covalent organic frameworks (COFs), as porous crystalline chiral materials, have become an important platform on which to explore new chiral photocatalytic materials due to their precise tunability, chiral structure, and function. This review highlights recent research progress on chiral COFs and their crystalline composites, evaluating their application as catalysts in asymmetric photocatalytic organic transformations in terms of their structure. Finally, the limitations and challenges of chiral COFs in asymmetric photocatalysis are discussed, with future opportunities for research being identified.

With worldwide cultivation, the faba bean (Vicia faba L.) stands as one of the most vital cool-season legume crops, serving as a major component of food security. China leads global faba bean production in terms of both total planting area and yield, with major production hubs in Yunnan, Sichuan, Jiangsu, and Gansu provinces. The faba bean viruses have caused serious yield losses in these production areas, but previous researches have not comprehensively investigated this issue. In this study, we collected 287 faba bean samples over three consecutive years from eight provinces/municipalities of China. We employed small RNA sequencing, RT-PCR, DNA sequencing, and phylogenetic analysis to detect the presence of viruses and examine their incidence, distribution, and genetic diversity. We identified a total of nine distinct viruses: bean yellow mosaic virus (BYMV, Potyvirus), milk vetch dwarf virus (MDV, Nanovirus), vicia cryptic virus (VCV, Alphapartitivirus), bean common mosaic virus (BCMV, Potyvirus), beet western yellows virus (BWYV, Polerovirus), broad bean wilt virus (BBWV, Fabavirus), soybean mosaic virus (SMV, Potyvirus), pea seed-borne mosaic virus (PSbMV, Potyvirus), and cucumber mosaic virus (CMV, Cucumovirus). BYMV was the predominant virus found during our sampling, followed by MDV and VCV. This study marks the first reported detection of BCMV in Chinese faba bean fields. Except for several isolates from Gansu and Yunnan provinces, our sequence analysis revealed that the majority of BYMV isolates contain highly conserved nucleotide sequences of coat protein (CP). Amino acid sequence alignment indicates that there is a conserved NAG motif at the N-terminal region of BYMV CP, which is considered important for aphid transmission. Our findings not only highlight the presence and diversity of pathogenic viruses in Chinese faba bean production, but also provide target pathogens for future antiviral resource screening and a basis for antiviral breeding.

This study investigated rice straw hydrothermal carbonization (HTC) in water, optimizing operating conditions to enhance solid carbon content and nitrogen content in hydrochar. Additionally, we conducted hydrothermal co-carbonization (co-HTC) of rice straw and acid whey, achieving significant improvements in hydrochar properties. Co-HTC resulted in a 53.6% increase in HHVs, 20.0% higher yield, and a 42.7% rise in carbon content, accompanied by notable reductions in ash content. Nitrogen content increased by 26.0%, P content by 12.7 times, and K content by 27.6%. Analytical techniques revealed promising modifications, indicating potential applications of hydrochar in solid fuel or organic fertilizers, thus contributing to a circular bioeconomy in agricultural waste management.

Consumer privacy information is used to target persuasive advertising in E-commerce, which raises consumer privacy concern. Consumer privacy concern is relative to consumer’s intrinsic privacy concern and social concern over the application of consumer privacy information, known as the anchoring effect of privacy. The anchoring effect of privacy influences targeted persuasive advertising competition. With a game-theoretical model, this paper studies how asymmetric duopolistic firms compete with targeted persuasive advertising considering the anchoring effect of privacy. The results indicate that when the advantageous firm increases its advertising level, the advantageous firm gets more profit, and the disadvantageous firm gets less profit only if the anchoring effect of privacy is greater than zero. Otherwise, the disadvantageous firm gets more profit, but the advantageous firm gets less profit. Then, in equilibrium, the increase in the expected anchoring effect of privacy, expected consumer’s intrinsic privacy concern, and advertising influence power reinforce the competition asymmetry. Whereas, the increase in social concern over the application of consumer privacy information weakens the competition asymmetry.