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Erhualian pigs exhibit one of the highest reproductive rates globally, and cryptorchidism is a crucial factor affecting reproductive abilities of boars. This investigation focused on cryptorchid tissues from Erhualian pigs, where the histological structure of cryptorchidism was observed using specialized staining. In addition, protein expression of P53/NF-κB in cryptorchid tissues was assessed using Western blot and immunohistochemistry. In comparison to normal Erhualian testes, Masson's trichrome staining indicated a reduction in collagen fibers in the connective tissue and around the basal membrane of the seminiferous tubules in cryptorchid testes. Moreover, collagen fiber distribution was observed to be disordered. Verhoeff Van Gieson (EVG) and argyrophilic staining demonstrated brownish-black granular nucleoli organized regions in mesenchymal cells and germ cells. When compared to normal testicles, the convoluted seminiferous tubules of cryptorchids exhibited a significantly reduced number and diameter (p < 0.01). Notably, VEGF/EGFR and P53/NF-κB expression in cryptorchidism significantly differed from that in normal testes. In particular, the expression of VEGF and P53 in cryptorchid tissues was significantly higher than that in normal testes tissues, whereas the expression of EGFR in cryptorchid tissues was significantly lower than that in normal testes tissues (all p < 0.01). NF-κB expressed no difference in both conditions. The expressions of VEGF and NF-κB were observed in the cytoplasm of testicular Leydig cells and spermatogenic cells, but they were weak in the nucleus. EGFR and P53 were more positively expressed in the cytoplasm of these cells, with no positive expression in the nucleus. Conclusion: There were changes in the tissue morphology and structure of the cryptorchid testis, coupled with abnormally high expression of VEGF and P53 proteins in Erhualian pigs. We speculate that this may be an important limiting factor to fecundity during cryptorchidism. [ABSTRACT FROM AUTHOR]

To investigate the effect of n-butanol on postharvest membrane lipid metabolism of Hami melon (Cucumis melo 'Hami'), the fruits were soaked in a 1.0% solution of n-butanol for 30 min with water as the control. Symptoms of chilling injury were observed regularly, and the indices related to permeability and membrane lipid metabolism of pericarp cells were measured. The results showed that treatment with n-butanol inhibited the increase in chilling injury index, membrane permeability, and malondialdehyde content of Hami melon fruits, promoted an increase in the contents of phosphatidyl alcohol and unsaturated fatty acids, such as linoleic acid, linolenic acid, oleic acid (except 14 d), and erucic acid (28–42 d), and decreased the content of saturated fatty acids, stearic acid (0–28 d), phosphatidic acid (except for 21 d), and the key enzymes of membrane lipid metabolism compared with the control. The activities of phospholipase D (PLD) and lipoxygenase (LOX) and the downregulation of the levels of expression CmPLD-β and CmLOX (42 d only) genes reduced the chilling injury index of Hami melon and alleviated the further expansion of chilling injury symptoms in the fruits. We also cloned the key gene of membrane lipid metabolism CmPLD-β, which was obtained by pre-transcriptome screening of the pericarp. We found that CmPLD-β of Hami melon had the closest affinity with cucumber (CsXP5), indicating that the CmPLD-β gene of Hami melon was functionally similar to that of cucumber. In addition, a two-fold alignment analysis of CmPLD-β and CmXP5 base sequences indicated that the base sequences of the two promoter regions differed from each other. [ABSTRACT FROM AUTHOR]

To help intelligent manufacturing enterprises lower their confusion in RFID investment and improve their performance through a prior understanding of the RFID influence, given the moderating of entrepreneurship, a dynamic capability theory-based conceptual model is proposed by us. Then, through a questionnaire survey, measurable indicators are effectively selected. Next, AMOS method-based modeling is put forward to analyze the moderating effect and mediating effect to test the research hypotheses. The results show, firstly, that the most significant variables are the "consistent investment" and the "management decision-making ability". Besides, different from the view of cost performance, the best reflected factors of enterprise performance in "intelligent manufacturing" are "product innovation speed and product market share". Secondly, proper RFID investment can have a positive impact on enterprise performance only if it is converted into intelligent manufacturing capability (mediating variable), which hints at the true mediating effect. Moreover, Entrepreneurship can positively moderate the RFID's influence on an enterprise's intelligent manufacturing capability, but not on the enterprise performance. Namely, the moderated mediating effect of enterprise's intelligent manufacturing capability is tenable. Generally, reasonable RFID investment in Chinese enterprises can promote intelligent manufacturing capability to improve the "intelligent manufacturing" performance. All these influence relations also vary with different entrepreneurships. [ABSTRACT FROM AUTHOR]

A mitochondria-targeted NIR probe based on the FRET mechanism was developed. It shows ultra-large Stokes shifts (460 nm) and emission shifts (285 nm). Furthermore, we also realized the imaging of SO2 in living SKOV-3 cells, zebrafish and living mice which may be useful for understanding the biological roles of SO2 in mitochondria and in vivo. [ABSTRACT FROM AUTHOR]

Under the background of climate warming, the occurrence of extreme events upstream of the Yellow River Basin has increased significantly. Extreme precipitation tends to be even more intense, and occurs more frequently. The impacts of various extreme weather and climate events in the basin have become increasingly complex, which is increasingly difficult to cope with and affects the basin's long-term stability and ecological security. Based on the daily precipitation data of 33 meteorological stations in the upper reaches of the Yellow River Basin from 1961 to 2021, this paper analyzes the characteristics of rainstorm intensity. Moreover, combined with the simulation results of 10 global climate models of the Coupled Model Intercomparison Project (CMIP6) and the social and economic prediction data from SSPs, it analyzes the possible changes of rainstorm disaster risk in the upper reaches of the Yellow River Basin in the 21st century, under the three emission scenarios of SSP126, SSP245, and SSP370. The results show that the precipitation in the upstream area of the Yellow River Basin is increasing at a rate of 8.1 mm per 10 years, and the number of rainstorm processes and their indicators is increasing, which indicates an increase in the extremeness of precipitation; the rainstorm process intensity index shows an increasing trend, especially in the northeast region with a concentrated population and economy, where the rainstorm process intensity index is high; it is estimated that the number of rainstorm days in low-, medium-, and high-risk scenarios will increase, which leads to an increase in the social risk by at least 60% by around 2050 (2036–2065); with the increasing disaster risk, the population exposure to rainstorm disasters is also on the rise. If no measures are taken, the population exposure will increase to 7.316 million people per day by around 2050, increasing by more than double, especially in the northeast. This study shows that, with the increasing rainstorm disaster risk and population exposure in the upper reaches of the Yellow River Basin, relevant measures need to be taken to ensure the safety of people's lives and property. [ABSTRACT FROM AUTHOR]

To solve the problem of the redundant number of training samples in a correlation filter-based tracking algorithm, the training samples were implicitly extended by circular shifts of the given target patches, and all the extended samples were used as negative samples for the fast online learning of the filter. Since all these shifted patches were not true negative samples of the target, the tracking process suffered from boundary effects, especially in challenging situations such as occlusion and background clutter, which can significantly impair the tracking performance of the tracker. Spatial regularization in the SRDCF tracking algorithm is an effective way to mitigate boundary effects, but it comes at the cost of highly increased time complexity, resulting in a very slow tracking speed of the SRDCF algorithm that cannot achieve a real-time tracking effect. To address this issue, we proposed a fast-tracking algorithm based on spatially regularized correlation filters that efficiently optimized the solved filters by replacing the Gauss–Seidel method in the SRDCF algorithm with the alternating direction multiplier method. The problem of slow speed in the SRDCF tracking algorithm improved, and the improved FSRCF algorithm achieved real-time tracking. An adaptive update mechanism was proposed by using the feedback from the high confidence tracking results to avoid model corruption. That is, a robust confidence evaluation criterion was introduced in the model update phase, which combined the maximum response criterion and the average peak correlation energy APCE criterion to determine whether to update the filter, thereby avoiding filter model drift and improving the target tracking accuracy and speed. We conducted extensive experiments on datasets OTB-2015, OTB-2013, UAV123, and TC128, and the experimental results show that the proposed algorithm exhibits a more stable and accurate tracking performance in the presence of occlusion and background clutter during tracking. [ABSTRACT FROM AUTHOR]

Aiming at the problems of target model drift or loss of target tracking caused by serious deformation, occlusion, fast motion, and out of view of the target in long-term moving target tracking in complex scenes, this paper presents a robust multi-feature single-target tracking algorithm based on a particle filter. The algorithm is based on the correlation filtering framework. First, to extract more accurate target appearance features, in addition to the manual features histogram of oriented gradient features and color histogram features, the depth features from the conv3–4, conv4–4 and conv5–4 convolutional layer outputs in VGGNet-19 are also fused. Secondly, this paper designs a re-detection module of a fusion particle filter for the problem of how to return to accurate tracking after the target tracking fails, so that the algorithm in this paper can maintain high robustness during long-term tracking. Finally, in the adaptive model update stage, the adaptive learning rate update and adaptive filter update are performed to improve the accuracy of target tracking. Extensive experiments are conducted on dataset OTB-2015, dataset OTB-2013, and dataset UAV123. The experimental results show that the proposed multi-feature single-target robust tracking algorithm with fused particle filtering can effectively solve the long-time target tracking problem in complex scenes, while showing more stable and accurate tracking performance. [ABSTRACT FROM AUTHOR]

Ion-exchange membranes (IEMs) represent a key component in various electrochemical energy conversion and storage systems. In this study, electrochemical impedance spectroscopy (EIS) was used to investigate the effects of structural changes of anion exchange membranes (AEMs) on the bulk membrane and interface properties as a function of solution pH. The variations in the physico/electrochemical properties, including ion exchange capacity, swelling degree, fixed charge density, zeta potentials as well as membrane and interface resistances of two commercial AEMs and cation exchange membranes (CEMs, as a control) were systematically investigated in different pH environments. Structural changes of the membrane surface were analyzed by Fourier transform infrared and X-ray photoelectron spectroscopy. Most notably, at high pH (pH > 10), the membrane (Rm) and the diffusion boundary layer resistances (Rdbl) increased for the two AEMs, whereas the electrical double layer resistance decreased simultaneously. This increase in Rm and Rdbl was mainly attributed to the deprotonation of the tertiary amino groups (-NR2H+) as a membrane functionality. Our results show that the local pH at the membrane-solution interface plays a crucial role on membrane electrochemical properties in IEM transport processes, particularly for AEMs. [ABSTRACT FROM AUTHOR]

Wheat is a major staple food crop worldwide, due to its total yield and unique processing quality. Its grain yield and quality are threatened by Fusarium head blight (FHB), which is mainly caused by Fusarium graminearum. Salicylic acid (SA) has a strong and toxic effect on F. graminearum and is a hopeful target for sustainable control of FHB. F. graminearum is capable of efficientdealing with SA stress. However, the underlying mechanisms remain unclear. Here, we characterized FgMFS1 (FGSG_03725), a major facilitator superfamily (MFS) transporter gene in F. graminearum. FgMFS1 was highly expressed during infection and was upregulated by SA. The predicted three-dimensional structure of the FgMFS1 protein was consistent with the schematic for the antiporter. The subcellular localization experiment indicated that FgMFS1 was usually expressed in the vacuole of hyphae, but was alternatively distributed in the cell membrane under SA treatment, indicating an element of F. graminearum in response to SA. ΔFgMFS1 (loss of function mutant of FgMFS1) showed enhanced sensitivity to SA, less pathogenicity towards wheat, and reduced DON production under SA stress. Re-introduction of a functional FgMFS1 gene into ∆FgMFS1 recovered the mutant phenotypes. Wheat spikes inoculated with ΔFgMFS1 accumulated more SA when compared to those inoculated with the wild-type strain. Ecotopic expression of FgMFS1 in yeast enhanced its tolerance to SA as expected, further demonstrating that FgMFS1 functions as an SA exporter. In conclusion, FgMFS1 encodes an SA exporter in F. graminearum, which is critical for its response to wheat endogenous SA and pathogenicity towards wheat. [ABSTRACT FROM AUTHOR]

Currently, many community detection methods are proposed in the network science field. However, most contemporary methods only employ modularity to detect communities, which may not be adequate to represent the real community structure of networks for its resolution limit problem. In order to resolve this problem, we put forward a new community detection approach based on a differential evolution algorithm (CDDEA), taking into account modularity density as an optimized function. In the CDDEA, a new tuning parameter is used to recognize different communities. The experimental results on synthetic and real-world networks show that the proposed algorithm provides an effective method in discovering community structure in complex networks. [ABSTRACT FROM AUTHOR]

Composite nanoarchitectures represent a class of nanostructured entities that integrates various dissimilar nanoscale building blocks including nanoparticles, nanowires, and nanofilms toward realizing multifunctional characteristics. A broad array of composite nanoarchitectures can be designed and fabricated, involving generic materials such as metal, ceramics, and polymers in nanoscale form. In this review, we will highlight the latest progress on composite nanostructures in our research group, particularly on various metal oxides including binary semiconductors, ABO(3)-type perovskites, A(2)BO(4) spinels and quaternary dielectric hydroxyl metal oxides (AB(OH)(6)) with diverse application potential. Through a generic template strategy in conjunction with various synthetic approaches- such as hydrothermal decomposition, colloidal deposition, physical sputtering, thermal decomposition and thermal oxidation, semiconductor oxide alloy nanowires, metal oxide/perovskite (spinel) composite nanowires, stannate based nanocompostes, as well as semiconductor heterojunction-arrays and networks have been self-assembled in large scale and are being developed as promising classes of composite nanoarchitectures, which may open a new array of advanced nanotechnologies in solid state lighting, solar absorption, photocatalysis and battery, auto-emission control, and chemical sensing.