Search Results (482)

BODIPY (Boron-Dipyrromethene) dyes have emerged as versatile fluorescent probes in cellular imaging and therapeutic applications owing to their unique chemical properties, including high fluorescence quantum yield, strong extinction coefficients, and remarkable photostability. This review synthesizes the recent advancements in BODIPY dyes, focusing on their deployment in biological imaging and therapy. The exceptional ability of BODIPY dyes to selectively stain cellular structures enables precise visualization of lipids, proteins, and nucleic acids within live and tumor cells, thereby facilitating enhanced understanding of biochemical processes. Moreover, BODIPY derivatives are increasingly utilized in Photodynamic therapy (PDT) and Photothermal therapies (PTT) for targeting cancer cells, where their capability to generate cytotoxic reactive oxygen species upon light activation offers a promising approach to tumor treatment. Recently, BODIPY derivatives have been used for Boron Neutron Capture Therapy (BNCT) for various tumors, and it is a growing research field. Advancements in nanotechnology have allowed the fabrication of BODIPY dye-based nanomedicines, either alone or with the use of metallic nanoparticles as a matrix offering the development of a new class of bioimaging and theragnostic agents. This review also discusses innovative BODIPY-based formulations and strategies that amplify therapeutic efficacy while minimizing adverse effects, underscoring the potential of these dyes as integral components in next-generation diagnostic and therapeutic modalities. By summarizing current research and future perspectives, this review highlights the critical importance of BODIPY dyes in advancing the fields of cellular imaging and treatment methodologies. Full article

This work presents the general mathematical frameworks of the “First and Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integral Equations of Volterra Type” designated as the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies, respectively. Using a single large-scale (adjoint) computation, the 1st-FASAM-NIE-V enables the most efficient computation of the exact expressions of all first-order sensitivities of the decoder response to the feature functions and also with respect to the optimal values of the NIE-net’s parameters/weights after the respective NIE-Volterra-net was optimized to represent the underlying physical system. The computation of all second-order sensitivities with respect to the feature functions using the 2nd-FASAM-NIE-V requires as many large-scale computations as there are first-order sensitivities of the decoder response with respect to the feature functions. Subsequently, the second-order sensitivities of the decoder response with respect to the primary model parameters are obtained trivially by applying the “chain-rule of differentiation” to the second-order sensitivities with respect to the feature functions. The application of the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies is illustrated by using a well-known model for neutron slowing down in a homogeneous hydrogenous medium, which yields tractable closed-form exact explicit expressions for all quantities of interest, including the various adjoint sensitivity functions and first- and second-order sensitivities of the decoder response with respect to all feature functions and also primary model parameters. Full article

In one of our previous papers, we obtained a general class of potentials inside the nucleus, such that the singular solution of the Dirac equation for the S-states of hydrogen atoms outside the nucleus can be matched with the corresponding regular solution inside the nucleus (the proton) at the boundary. The experimental charge density distribution inside the proton generates a particular case of such potentials inside the proton. In this way, the existence of the second kind of hydrogen atom was predicted: atoms having only S-states. This theoretical prediction was then evidenced by several different types of atomic experiments and by astrophysical observations. In the present paper we provide the following new results. First, we show that the solution of the Dirac equation inside the proton can be (and is) found within the class of functions that are non-analytic at r = 0—in distinction to the traditional practice of limiting the search for the solution by the class of analytic functions. We demonstrate that this non-analytic solution inside the proton can be matched at the proton boundary R with the corresponding singular solution outside the proton regardless of the particular value of R. Second, we show that the interior and exterior solutions are scale-invariant with respect to the change of the boundary R between these two regions. Such invariance is the manifestation of a new symmetry—in addition to the previously discussed symmetries of the Dirac equation in the literature. Third, based on the new, more accurate results for the wave function inside and outside the proton, we revisit the resolution of the neutron lifetime puzzle initially outlined in our previous papers. On the basis of the more accurate calculations, we reconfirm that (A) the 2-body decay of neutrons produces overwhelmingly the SFHA (rather than the usual hydrogen atoms) and (B) the strengthened-in-this-way branching ratio for the 2-body decay of neutrons (compared to the 3-body decay) is in excellent agreement with the branching ratio required for reconciling the neutron lifetime values measured in the trap and beam experiments, so that the neutron lifetime puzzle seems to be indeed resolved in this way. Full article

We describe the quark substructure of hadrons and the equation of state of high-density neutron star matter by using the Nambu–Jona-Lasinio (NJL) model, which is an effective quark theory based on QCD. The interaction between quarks fully respects the chiral and flavor symmetries. Guided by the success of various low-energy theorems, we assume that the explicit breaking of these symmetries occurs only via the current quark masses, and all other symmetry breakings are of dynamical nature. In order to take into account the effects of the finite quark core sizes of the baryons on the equation of state, we make use of an excluded volume framework that respects thermodynamic consistency. The effects generated by the swelling quark cores generally act repulsively and lead to an increase in the pressure with increasing baryon density. On the other hand, in neutron star matter, these effects also lead to a decrease in the density window where hyperons appear because it becomes energetically more favorable to convert the faster moving nucleons into hyperons. Our quantitative analysis shows that the net effect of the excluded volume is too small to solve the long-standing “hyperon puzzle”, which is posed by the large observed masses of neutron stars. Thus, the puzzle persists in a relativistic effective quark theory which takes into account the short-range repulsion between baryons caused by their finite and swelling quark core sizes in a phenomenological way. Full article

The bacterium Bacillus anthracis secretes three protein exotoxins: Protective Antigen 83 (PA83), Lethal Factor (LF), and Edema Factor (EF). A cleaved form of PA83 (PA63) aids LF and EF entry into the cytoplasm, which leads to anthrax-induced cell death. The Protein Data Bank (PDB) has more than 25 structures of LF: the monomer alone, bound with inhibitors, or bound to PA63. The structures are all—with only minor shifts of a few Ångströms—nearly congruent. We have measured the structure of LF at equilibrium in D₂O solution by small-angle neutron scattering (SANS). The shape is modeled well by a parallelepiped (all angles 90°) with dimensions of 12 Å × 49 Å × 129 Å. For a protein with a typical density of 1.4, the molecular weight would be between 55 and 94 kDa, which is comparable to that of the 90.2 kDa monomer. However, the LF crystal structure PDB 1pwu (a generally V-shaped molecule with equal arm lengths ≈ 70 Å) with the same model fits the dimensions 30 Å × 48 Å × 104 Å. Given the large changes in the long and short dimensions, straightforward physical modeling of the solution structure from the crystal form is unable to match the SANS results. Full article

In the current context of the global energy landscape, China is facing a growing challenge in oil and gas exploration and development. It is difficult to evaluate the log data because of the lithological composition of igneous rocks, which displays an unparalleled degree of complexity and unpredictability. Against this backdrop, this study deploys advanced multifractal detrended fluctuation analysis (MF-DFA) to comprehensively analyze key parameters within igneous rock logging data, including natural gamma-ray logging, resistivity logging, compensated neutron logging, and acoustic logging. The results unequivocally demonstrate that these logging data possess distinct multifractal characteristics. This multifractality serves as a powerful tool to elucidate the inherent complexity, heterogeneity, and structural and property variations in igneous rocks caused by diverse geological processes and environmental changes during their formation and evolution, which is crucial for understanding the subsurface reservoir behavior. Subsequently, through a series of rearrangement sequences and the replacement sequence on the original logging data, we identify that the probability density function and long-range correlation are the fundamental sources of the observed multifractality. These findings contribute to a deeper theoretical understanding of the data-generating mechanisms within igneous rock formations. Finally, multifractal detrended cross-correlation analysis (MF-DCCA) is employed to explore the cross-correlations among different types of igneous rock logging data. We uncover correlations among different igneous rocks’ logging data. These parameters exhibit different properties. There are negative long-range correlations between natural gamma-ray logging and resistivity logging, natural gamma-ray logging and compensated neutron logging in basalt, and resistivity logging and compensated neutron logging in diabase. The logging data on other igneous rocks have long-range correlations. These correlation results are of great significance as they provide solid data support for the formulation of oil and gas exploration and development plans. Full article

The advent of third-generation (3G) gravitational-wave (GW) detectors opens new opportunities for multi-messenger observations of binary neutron star merger events, holding significant potential for probing the history of cosmic expansion. In this paper, we investigate the holographic dark energy (HDE) model by using the future GW standard siren data observed from the 3G GW detectors and the short $\gamma$-ray burst THESEUS-like detector joint observations. We find that GW data alone can achieve a relatively precise estimation of the Hubble constant, with precision of $0.2$–$0.6\%$, but its ability to constrain other cosmological parameters remains limited. Nonetheless, since the GW data can break parameter degeneracies generated by the mainstream EM observations, CMB + BAO + SN (CBS), GW standard sirens play a crucial role in enhancing the accuracy of parameter estimation. With the addition of GW data to CBS, the constraints on cosmological parameters $H_0$, c and ${\Omega }_{\mathrm{m}}$ can be improved by 63–$88\%$, 27–$44\%$ and 55–$70\%$. In summary, observations of GW standard sirens from 3G GW detectors could be pivotal in probing the fundamental nature of dark energy. Full article

One of the primary challenges for future nuclear fusion power plants is understanding how neutron irradiation affects reactor materials. To tackle this issue, the IFMIF-DONES project aims to build a facility capable of generating a neutron source in order to irradiate different material samples. This will be achieved by colliding a deuteron beam with a lithium jet. In this work, within the DONES-FLUX project, deep learning surrogate models are applied to the design and optimization of the IFMIF-DONES linear accelerator. Specifically, neural operators are employed to predict deuteron beam envelopes along the longitudinal axis of the accelerator and neutron irradiation effects at the end, after the beam collision. This approach has resulted in models that are able of approximating complex simulations with high accuracy (less than 17% percentage error for the worst case) and significantly reduced inference time (ranging from 2 to 6 orders of magnitude) while being differentiable. The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. Overall, these results demonstrate the synergy between deep learning models and differentiable programming, offering a promising collaboration among physicists and computer scientists to further improve the design and optimization of IFMIF-DONES and other accelerator facilities. This research will lay the foundations for future projects, where optimization efforts with differentiable programming will be performed. Full article

We present a theoretical framework that allows one to make an explicit connection between the phenomenology of QCD, namely the properties of the gluon correlator and Wilson loops, and a particular relativistic model for the description of nuclear matter and neutron stars: the chiral confining model. Starting with the field correlator method, which explicitly and simultaneously incorporates confinement and chiral symmetry breaking, we describe how to obtain the response of the composite nucleon to the nuclear scalar field, as well as the relative role of confinement and chiral symmetry breaking in in-medium nucleon mass evolution, thereby generating the three-body forces needed for the saturation mechanism. Full article

A thermal neutron-absorbing metal matrix composite (MMC) comprised of Al₃Hf particles in an aluminum matrix was developed to filter out thermal neutrons and create a fast flux environment for material testing in a mixed-spectrum nuclear reactor. Intermetallic Al₃Hf particles capture thermal neutrons and are embedded in a highly conductive aluminum matrix that provides conductive cooling of the heat generated due to thermal neutron capture by the hafnium. These Al₃Hf-Al MMCs were fabricated using powder metallurgy via hot pressing. The specimens were neutron-irradiated to between 1.12 and 5.38 dpa and temperatures ranging from 286 °C to 400 °C. The post-irradiation examination included microstructure characterization using transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy. This study reports the microstructural observations of four irradiated samples and one unirradiated control sample. All the samples showed the presence of oxide at the particle–matrix interface. The irradiated specimens revealed needle-like structures that extended from the surface of the Al₃Hf particles into the Al matrix. An automated segmentation tool was implemented based on a YOLO11 computer vision-based approach to identify dislocation lines and loops in TEM images of the irradiated Al-Al₃Hf MMCs. This work provides insight into the microstructural stability of Al₃Hf-Al MMCs under irradiation, supporting their consideration as a novel neutron absorber that enables advanced spectral tailoring. Full article

Recent studies have focused on how spinning black holes (BHs) within a binary system containing a strongly magnetized neutron star, then immersed in external magnetic fields, can acquire charge through mechanisms like the Wald process and how this charge could power pulsar-like electromagnetic radiation. Those objects called “Black hole pulsar” mimic the behaviour of a traditional pulsar, and they can generate electromagnetic fields, such as magnetic dipoles. Charged particles within an accretion disk around the black hole would then be influenced not only by the gravitational forces but also by electromagnetic forces, leading to different geometries and dynamics. In this context, we focus here on the interplay of the magnetic dipole and the accretion disk. We construct the equilibrium structures of non-conducting charged perfect fluids orbiting Kerr black holes under the influence of a dipole magnetic field aligned with the rotation axis of the BH. The dynamics of the accretion disk in such a system are shaped by a complex interplay between the non-uniform, non-Keplerian angular momentum distribution, the black hole’s induced magnetic dipole, and the fluid’s charge. We show how these factors jointly influence key properties of the disk, such as its geometry, aspect ratio, size, and rest mass density. Full article

The liquid-fueled molten salt reactor (MSR) is one of the candidate reactors for the Generation IV advanced nuclear power systems, which utilizes flowing liquid molten salt as both fuel and coolant. In transients of liquid-fueled MSRs, the distribution change in the delayed neutron precursors (DNPs) in the primary loop has an important impact on system safety analysis. In order to analyze and evaluate this effect, the RELAP5-TMSR code with a 1-D DNP transport model was used to model the Molten Salt Breeder Reactor (MSBR), and several representative transient scenarios, including the loss of primary flow, increase in primary flow, loss of secondary flow, reactivity perturbation, and load change, were simulated and analyzed. The results show that the DNP distribution changes obviously during primary flow transients, especially during the loss of primary flow. Besides, the power response trends at different power levels during the loss of primary flow are different. The analysis results reveal the steady-state and dynamic characteristics of the DNP distribution, indicating that the DNP distribution, temperature feedback, and reactor power are strongly coupled, which has significant implications for the design and safety analysis of liquid-fueled MSRs. Full article

Boron Neutron-Capture Therapy (BNCT) is a form of radiation therapy that relies on the highly localized and enhanced biological effects of the ¹⁰B neutron capture (BNC) reaction products to selectively kill cancer cells. The efficacy of BNCT is, therefore, strongly dependent on the ¹⁰B spatial microdistribution at a subcellular level. Fluorescent Nuclear Track Detectors (FNTDs) could be a promising technology for measuring ¹⁰B microdistribution. They allow the measurement of the tracks of charged particles, and their biocompatibility allows cell samples to be deposited and grown on their surfaces. If a layer of borated cells is deposited and irradiated by a neutron field, the energy deposited by the BNC products and their trajectories can be measured by analyzing the corresponding tracks. This allows the reconstruction of the position where the measured particles were generated, hence the microdistribution of ¹⁰B. With respect to other techniques developed to measure ¹⁰B microdistribution, FNTDs would be a non-destructive, biocompatible, relatively easy-to-use, and accessible method, allowing the simultaneous measurement of the ¹⁰B microdistribution, the LET of particles, and the evolution of the related biological response on the very same cell sample. An FNTD was tested in three irradiation conditions to study the feasibility of FNTDs for BNCT applications. The FNTD allowed the successful measurement of the correct alpha particle range and mean penetration depth expected for all the radiation fields employed. This work proved the feasibility of FNTD in reconstructing the tracks of the alpha particles produced in typical BNCT conditions, thus the ¹⁰B microdistribution. Further experiments are planned at the University of Pavia’s LENA (Applied Nuclear Energy Laboratory) to test the final set-up coupling the FNTD with borated cell samples. Full article

With the increasing global demand for sustainable energy, the importance of advanced nuclear technologies, such as fourth-generation reactors, has become increasingly prominent. Fourth-generation reactors often use non-water coolants, among which liquid lead and lead–bismuth eutectics (LBEs) are highly promising, making lead-cooled fast reactors (LFRs) a popular area of research internationally. On the basis of extensive analysis and comparison conducted previously, this article summarizes and analyzes the advantages, problems, and differences in lead and LBE as LFR coolants. Overall, both lead and LBE have excellent neutronic characteristics, good heat transfer performance, and chemical inertness, and make LFRs highly efficient in nuclear fuel utilization, inherently safe, and relatively simplified in design. However, both of them corrode materials severely and produce highly toxic ²¹⁰Po, which are the problems that need to be considered for further engineering development. Moreover, LBE has a lower melting point, which allows a wider temperature range and lower insulation requirements in its design, making it easier to achieve engineering and miniaturization under the same conditions. Lead has a lower cost, is less corrosive to materials, and produces less ²¹⁰Po, which makes it a more ideal coolant for future development. Full article

In this study, the microstructure and corrosion behavior of gas tungsten arc (GTA) welds of borated stainless steel (BSS) with a boron content of 1.62 wt.% were investigated using various filler metals. The filler metals used in this study were 308L, 309L, and 310 without the B component. A small amount of the B component was observed in the weld metal (WM) of all specimens, even though none of the filler wires contained boron. This result was caused by the dilution of the B component from the BM into the WM by the welding heat. The segregation of boron in the WM resulted in Cr-depleted areas, which negatively affected the corrosion resistance of the welded specimens. The corrosion resistance of 308L WM with the highest fraction of B components was the most deteriorated, whereas 309L WM with the lowest boron content exhibited the best corrosion resistance. Using a filler metal without the B component is expected to effectively improve the weldability and corrosion resistance of BSS; however, it can also reduce the neutron absorption capacity. Therefore, for BSS to be used as a spent nuclear fuel storage container material, the boron content of the filler metal must be carefully considered. This study provides a foundation for research aimed at improving the development and applicability of filler metals in borated stainless steel and makes it competitive for application in fourth-generation nuclear power systems. Full article