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A generation method of new metric in the case of static spherically symmetric space-time is derived. Using this approach, we construct a metric which describes Euler–Heisenberg black hole surrounded by perfect fluid dark matter and investigate its optical and thermodynamic properties. We found that radius of shadow will increase with the increase of dark matter effect, and more strong dark matter will diminish the light intensity of accretion disk generally. Moreover, in thermodynamics, when quantum electrodynamic parameter is positive, there will be a critical value of dark matter parameter, which determine the number of black hole’s critical points.

Alpine plants face intense ultraviolet (UV) radiation in high-altitude ecosystems, necessitating adaptive mechanisms like tyrosinase-mediated phenolic metabolism for UV protection. This study aimed to characterize the phenolic profile of Corallodiscus flabellatus (or C. flabellata) and elucidate its mechanistic interactions with tyrosinase under high-altitude environments with intense ultraviolet (UV) radiation. Two novel phenylethanoid glycosides (PhGs) and seven known compounds were isolated using silica gel, ODS, and preparative HPLC, with structures determined via NMR, HR-ESI-MS, and acid hydrolysis. Tyrosinase (EC 1.14.18.1) inhibition assays revealed divergent effects: compound 7 (containing a caffeoyl moiety) exhibited potent inhibition (IC50 = 0.23 μM), comparable to arbutin, while other PhGs displayed activation or biphasic responses. Molecular docking analysis demonstrated that compound 7 stabilized tyrosinase via π-π stacking with Phe264 and Cu2+ coordination, whereas activating compounds likely acted as substrates. These findings elucidate the dual regulatory function of PhGs, which activate tyrosinase to counteract acute ultraviolet-induced stress and inhibit its activity to attenuate oxidative overload, thereby advancing our understanding of alpine plant adaptation mechanisms.

We obtained the metric of the Schwarzschild-like black hole with loop quantum gravity (LQG) corrections in anti-de Sitter (AdS) space-time, under the assumption that the cosmological constant is decoupled in LQG. We investigated its thermodynamics, including the equation of state, criticality, heat capacity, and Gibbs free energy. The P - v graph was plotted, and the critical behavior was calculated. It was found that, due to the LQG effect, the quantum-corrected Schwarzschild-AdS black hole exhibits a critical point and a critical ratio of 7/18, which differs from the Reissner–Nordstr o ¨ m-AdS black hole’s ratio of 3/8 (the same as that of the Van der Waals system) slightly. However, there are still some similarities compared to the Van der Waals system, such as the same critical exponents and a similar P - v graph. Moreover, it is concluded that the energy-momentum tensor related to the black hole’s mass could violate the conventional first law of thermodynamics. This modified first law may violate the conservation of Gibbs free energy during the small black hole-large black hole phase transitions, potentially indicating the occurrence of the zeroth-order phase transition. The Joule–Thomson expansion was also studied. Interestingly, compared to the Schwarzschild-AdS black hole, the LQG effect leads to inversion points. The inversion curve divides the P , T coordinate system into two regions: a heating region and a cooling region, as shown in detail by the inversion curves and isenthalpic curves. The results indicated that there is a minimum inversion mass, below which any black hole will not possess an inversion point.

Patient-derived tumor organoids (PDOs) currently represent important modeling tools in pre-clinical investigation of malignancies. Organoid cultures conserve the genetic and phenotypic characteristics of the original tumor and maintain its heterogeneity, allowing their application in many research fields. PDOs derived from colorectal cancer (CRC) have been used for genetic modeling to investigate the function of driver genes. Some researchers have been exploring the value of CRC PDOs in chemotherapy, targeted therapy, and radiotherapy response prediction. The successful generation of PDOs derived from CRC could deepen our understanding of CRC biology and provide novel tools for cancer modeling, for realizing precision medicine by assessing specimens from individual patients ex vivo. The present review discusses recently reported advances in CRC PDOs and the challenges they face as pre-clinical models in CRC research.

Motivated by recent work on rotating black hole shadow (Chang and Zhu in Phys Rev D 101:084029, 2020), we investigate the shadow behaviours of rotating Hayward–de Sitter black hole for static observers at a finite distance in terms of astronomical observables. This paper uses the newly introduced distortion parameter (Chang and Zhu in Phys Rev D 102:044012, 2020) to describe the shadow’s shape quantitatively. We show that the spin parameter would distort shadows and the magnetic monopole charge would increase the degree of deformation. The distortion will increase as the distance between the observer and the black hole increases, and distortion reduces as the cosmological constant increases. Besides, the increase of the spin parameter, magnetic monopole charge and cosmological constant will cause the shadows shrunken.

Anthropogenic environments have been implicated in enrichment and exchange of antibiotic resistance genes and bacteria. Here we study the impact of confined and controlled swine farm environments on temporal changes in the gut microbiome and resistome of veterinary students with occupational exposure for 3 months. By analyzing 16S rRNA and whole metagenome shotgun sequencing data in tandem with culture-based methods, we show that farm exposure shapes the gut microbiome of students, resulting in enrichment of potentially pathogenic taxa and antimicrobial resistance genes. Comparison of students’ gut microbiomes and resistomes to farm workers’ and environmental samples revealed extensive sharing of resistance genes and bacteria following exposure and after three months of their visit. Notably, antibiotic resistance genes were found in similar genetic contexts in student samples and farm environmental samples. Dynamic Bayesian network modeling predicted that the observed changes partially reverse over a 4-6 month period. Our results indicate that acute changes in a human’s living environment can persistently shape their gut microbiota and antibiotic resistome. Environments where antibiotics are used indiscriminately exhibit microbial communities that can represent hot-spots of resistance gene enrichment, which in turn could spread to humans. Here, the authors characterize how exposure to swine farms environment lead to temporal changes in the gut microbiome and resistome of healthy veterinary students.

The existing tunnel construction causes stratum deformation, which in turn leads to additional deformation and internal force of the overlying pipeline, thus increasing the risk of pipeline accidents. Then, how to correctly calculate the deformation and internal force of pipeline is the key to pipeline safety evaluation. To this end, this study firstly used the Pasternak foundation beam model to simulate the interaction of pipeline and soil, and divided the pipeline into the void area (i.e., pipeline-soil detachment) and the coordination area (i.e., pipeline-soil is always deformed together) between pipeline and soil. The differential equation of pipeline deflection for the void area and the coordination area were established respectively, and the solutions of pipeline deflection, the internal force of pipeline and the width of pipeline-soil void area were presented. Subsequently, the accuracy of the proposed method was verified by comparing with the available model and field test data, and it is found that the calculation results are too conservative without considering the pipeline-soil voiding phenomenon. Finally, the detailed parametric analysis was conducted. The results show that the pipeline deflection decreases with the increase of the pipeline-tunnel spacing between pipeline and tunnel, the pipeline bending stiffness and the soil elastic modulus, but increases with the increase of the formation loss rate, and the width of pipeline-soil void area increases with the increase of the pipeline-tunnel spacing, the pipeline bending stiffness and the soil elastic modulus.

We briefly analyzed the equation of state and critical points of the quantum-corrected-AdS black hole and used the Melnikov method to study its thermal chaotic behavior in the extended phase space of flat, closed, and open universes. The results show that the black hole’s thermodynamic behavior is similar to that of the Van der Waals system. Although the critical ratios at the critical points in the three types of universes differ, they are all independent of the quantum correction parameter. Only an open universe can attain the critical ratio of 3 8 corresponding to the Van der Waals system, while in the other two universes, the critical ratio is always greater than this value. For chaos, time perturbations will lead to chaotic behavior when their amplitude exceeds a critical value that depends on the quantum correction parameter and the radius of the dust sphere in the FRW model. Based on this, we found that the chaotic behavior of the black hole varies across different universes depending on the quantum correction parameter, but this parameter always makes chaos more likely. Using the value of the quantum correction parameter determined by Meissner, chaos is always more difficult to occur in an open universe compared to the other two types of universes. Which universe is most prone to chaos depends on the radius of the dust sphere. Finally, chaotic behavior is always present under spatial perturbations.

This paper shows a 2-step procedure for obtaining a variable-bandwidth recursive digital filter whose structure contains cascaded second-order (2nd-order) sections. Such a cascade-form structure is insensitive to the round-off noises that come from filter-coefficient quantizations in hardware implementations. This paper also shows how to utilize a 2-step procedure to get a variable-bandwidth recursive filter that is absolutely stable. The first step (Step-1) of the 2-step procedure designs a series of constant-bandwidth filters for approximating a series of evenly discretized variable specifications, and the second step (Step-2) fits the coefficient values obtained from Step-1 by employing individual polynomials. To ensure the stability of the resultant constant-bandwidth filters in Step-1, coefficient transformations are first executed on the 2nd-order transfer function's denominator-coefficients, and then each coefficient of both numerator and transformed denominator is found as an individual polynomial. Once all the polynomials are obtained, the polynomials corresponding to the transformed denominator are further converted to composite functions for ensuring the stability. Hence, the 2-step procedure not only produces a cascade-form variable-bandwidth filter that has low quantization errors, but also ensures the stability. A lowpass example is included for verifying the achieved stability and showing the high approximation accuracy.

Zebrafish are widely used in vertebrate studies, yet minimally invasive individual tracking and identification in the lab setting remain challenging due to complex and time-variable conditions. Advancements in machine learning, particularly neural networks, offer new possibilities for developing simple and robust identification protocols that adapt to changing conditions. We demonstrate a rolling window training technique suitable for use with open-source convolutional neural networks (CNN) and vision transformers (ViT) that shows promise in robustly identifying individual maturing zebrafish in groups over several weeks. The technique provides a high-fidelity method for monitoring the temporally evolving zebrafish classes, potentially significantly reducing the need for new training images in both CNN and ViT architectures. To understand the success of the CNN classifier and inform future real-time identification of zebrafish, we analyzed the impact of shape, pattern, and color by modifying the images of the training set and compared the test results with other prevalent machine learning models.