Equivalence between two charged black holes in dynamics of orbits outside the event horizons

Using the FermiDirac distribution function, Balart and Vagenas gave a charged spherically symmetric regular black hole, which is a solution of Einstein field equations coupled to a nonlinear electrodynamics. In fact, the regular black hole is a Reissner-Nordstrom (RN) black hole when a metric function is given a Taylor expansion to first order approximations. It does not have a curvature singularity at the origin,but the RN black hole does. Both black hole metrics have horizons and similar asymptotic behaviors, and satisfy the weak energy conditions everywhere. They are almost the same in photon effective potentials, photon circular orbits and photon spheres outside the event horizons. There are relatively minor differences between effective potentials, stable circular orbits and innermost stable circular orbits of charged particles outside the event horizons of the two black holes immersed in external magnetic fields. Although the twomagnetized black holes allow different construction methods of explicit symplectic integrators, they exhibit approximately consistent results in the regular and chaotic dynamics of charged particles outside the event horizons. Chaos gets strong as the magnetic field parameter or the magnitude of negative Coulomb parameter increases, but becomes weak when the black hole charge or the positive Coulomb parameter increases. A variation of dynamical properties is not sensitive dependence on an appropriate increase of the black hole charge. The basic equivalence between the two black hole gravitational systems in the dynamics of orbits outside the event horizons is due to the two metric functions having an extremely small difference. This implies that the RN black hole is reasonably replaced by the regular black hole without curvature singularity in many situations.Comment: 18 pages, 12 figure

Corporate Credit Rating: A Survey

Corporate credit rating (CCR) plays a very important role in the process of contemporary economic and social development. How to use credit rating methods for enterprises has always been a problem worthy of discussion. Through reading and studying the relevant literature at home and abroad, this paper makes a systematic survey of CCR. This paper combs the context of the development of CCR methods from the three levels: statistical models, machine learning models and neural network models, summarizes the common databases of CCR, and deeply compares the advantages and disadvantages of the models. Finally, this paper summarizes the problems existing in the current research and prospects the future of CCR. Compared with the existing review of CCR, this paper expounds and analyzes the progress of neural network model in this field in recent years.Comment: 11 page

DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency

The combination of electronic health records (EHR) and medical images is crucial for clinicians in making diagnoses and forecasting prognosis. Strategically fusing these two data modalities has great potential to improve the accuracy of machine learning models in clinical prediction tasks. However, the asynchronous and complementary nature of EHR and medical images presents unique challenges. Missing modalities due to clinical and administrative factors are inevitable in practice, and the significance of each data modality varies depending on the patient and the prediction target, resulting in inconsistent predictions and suboptimal model performance. To address these challenges, we propose DrFuse to achieve effective clinical multi-modal fusion. It tackles the missing modality issue by disentangling the features shared across modalities and those unique within each modality. Furthermore, we address the modal inconsistency issue via a disease-wise attention layer that produces the patient- and disease-wise weighting for each modality to make the final prediction. We validate the proposed method using real-world large-scale datasets, MIMIC-IV and MIMIC-CXR. Experimental results show that the proposed method significantly outperforms the state-of-the-art models. Our implementation is publicly available at https://github.com/dorothy-yao/drfuse.Comment: Accepted by AAAI-2

Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management

Training-Free Semantic Segmentation via LLM-Supervision

Recent advancements in open vocabulary models, like CLIP, have notably advanced zero-shot classification and segmentation by utilizing natural language for class-specific embeddings. However, most research has focused on improving model accuracy through prompt engineering, prompt learning, or fine-tuning with limited labeled data, thereby overlooking the importance of refining the class descriptors. This paper introduces a new approach to text-supervised semantic segmentation using supervision by a large language model (LLM) that does not require extra training. Our method starts from an LLM, like GPT-3, to generate a detailed set of subclasses for more accurate class representation. We then employ an advanced text-supervised semantic segmentation model to apply the generated subclasses as target labels, resulting in diverse segmentation results tailored to each subclass's unique characteristics. Additionally, we propose an assembly that merges the segmentation maps from the various subclass descriptors to ensure a more comprehensive representation of the different aspects in the test images. Through comprehensive experiments on three standard benchmarks, our method outperforms traditional text-supervised semantic segmentation methods by a marked margin.Comment: 22 pages,10 figures, conferenc

Tuning Photophysical Properties And Improving Nonlinear Absorption Of Pt(ii) Diimine Complexes With Extended Pi-conjugation In The Acetylide Ligands

Two new Pt(II) 4,4\u27-di(5,9-diethyltridecan-7-yl)-2,2\u27-bipyridine complexes (1 and 2,) bearing 9,9-diethyl-2-ethynyl-7-(2-(4-nitrophenyl)ethynyl)-9H-fluorene ligand and N-(4-(2-(9,9-diethyl-7-ethynyl-9H-fluoren-2-yl)ethynyl)phenyl)-N-phenylbenzeneamine ligand, respectively, were synthesized and characterized. Their photophysical properties were investigated systematically by UV vis absorption, emission, and transient absorption (TA) spectroscopy, and the nonlinear absorption was studied by nonlinear transmission technique. Theoretical TD-DFT calculations using the CAM-B3LYP functional were carried out to determine the nature of the singlet excited electronic states and to assist in the assignment of significant transitions observed in experiments. Complex 1 exhibits an intense, structureless absorption band at ca. 397 nm in CH2Cl2 solution, which is attributed to mixed metal-to-ligand charge transfer ((MLCT)-M-1)/ligand-to-ligand charge transfer ((LLCT)-L-1)/intraligand charge transfer ((ILCT)-I-1)/(1)pi,pi* transitions, and two (MLCT)-M-1/(LLCT)-L-1 transitions in the 300-350 nm spectral region. Complex 2 possesses an intense acetylide ligand localized (1)pi,pi* absorption band at ca. 373 nm and a moderately intense (MLCT)-M-1/(LLCT)-L-1 tail above 425 nm in CH2Cl2. Both complexes are emissive in solution at room temperature, with the emitting state being tentatively assigned to the predominant (3)pi,pi* state for 1, whereas the emitting state of 2 exhibits a switch from (3)pi,pi* state in high-polarity solvents to (MLCT)-M-3/(LLCT)-L-3 state in low-polarity solvents. Both 1 and 2 exhibit strong singlet excited-state TA in the visible to NIR region, where reverse saturable absorption (RSA) is feasible. The spectroscopic studies and theoretical calculations indicate that the photophysical properties of these Pt complexes can be tuned drastically by extending the pi-conjugation of the acetylide ligands. In addition, strong RSA was observed at 532 nm for nanosecond (ns) laser pulses from 1 and 2, demonstrating that the RSA of the Pt(II) diimine complexes can be improved by extending the pi-conjugation of the acetylide ligands

A Biodegradable Polyethylenimine-Based Vector Modified by Trifunctional Peptide R18 for Enhancing Gene Transfection Efficiency In Vivo

Lack of capacity to cross the nucleus membrane seems to be one of the main reasons for the lower transfection efficiency of gene vectors observed in vivo study than in vitro. To solve this problem, a new non-viral gene vector was designed. First, a degradable polyethylenimine (PEI) derivate was synthesized by crosslinking low-molecular-weight (LMW) PEI with N-octyl-N-quaternary chitosan (OTMCS), and then adopting a designed trifunctional peptide (RGDC- TAT-NLS) with good tumor targeting, cell uptake and nucleus transport capabilities to modify OTMCS-PEI. The new gene vector was termed as OTMCS- PEI-R18 and characterized in terms of its chemical structure and biophysical parameters. Gene transfection efficiency and nucleus transport mechanism of this vector were also evaluated. The polymer showed controlled degradation and remarkable buffer capabilities with the particle size around 100–300 nm and the zeta potential ranged from 5 mV to 40 mV. Agraose gel electrophoresis showed that OTMCS-PEI-R18 could effectively condensed plasmid DNA at a ratio of 1.0. Besides, the polymer was stable in the presence of sodium heparin and could resist digestion by DNase I at a concentration of 63U DNase I/DNA. OTMCS-PEI-R18 also showed much lower cytotoxicity and better transfection rates compared to polymers OTMCS-PEI-R13, OTMCS-PEI and PEI 25 KDa in vitro and in vivo. Furthermore, OTMCS-PEI-R18/DNA complexes could accumulate in the nucleus well soon and not rely on mitosis absolutely due to the newly incorporated ligand peptide NLS with the specific nuclear delivery pathway indicating that the gene delivery system OTMCS-PEI-R18 could reinforce gene transfection efficiency in vivo

Study on Spatial Distribution of Soil Available Microelement in Qujing Tobacco Farming Area, China

AbstractDescriptive analysis characteristics and spatial variation characteristics of soil available microelements were studied based on SPSS and GIS Soil available microelements spatial distribution maps were created with ordinary Kriging method. The results indicate that, 7 available microelements in tobacco soil obey lognormal distribution, all the available microelements were intermediate variability; Anisotropic structure of available microelements of tobacco soil varies evidently, spatial variability of available B was mainly caused by random factors, and others’ spatial variability were caused by structural factors and random factors; Spatial distribution maps show that, available B was widely deficient in tobacco soil of Qujing farming area, ‘lower level’ and ‘low level’ taken 7.74% and 68.20%, respectively available Zn distribution was moderate, only 1.32% of the area lack of Zn, available Cu, available Fe and available Mn were extremely high in the whole extension, available Mo was deficient in part of the region with 28.38%, water soluble Cl was higher than critical value(30mgkg−1)in the most of Qujing farming area, which taken 38.86%

Concurrent nephrotic syndrome and acute renal failure caused by chronic lymphocytic leukemia (CLL): a case report and literature review

Kidney injury associated with lymphocytic leukemia (CLL) is typically caused by direct tumor infiltration which occasionally results in acute renal failure. Glomerular involvement presenting as proteinuria or even nephrotic syndrome is exceptionally rare. Here we report a case of 54-year-old male CLL patient with nephrotic syndrome and renal failure. The lymph node biopsy confirmed that the patients had CLL with remarkable immunoglobulin light chain amyloid deposition. The renal biopsy demonstrated the concurrence of AL amyloidosis and neoplastic infiltration. Combined treatment of fludarabine, cyclophosphamide and rituximab resulted in remission of CLL, as well as the renal disfunction and nephrotic syndrome, without recurrence during a 12-month follow-up. To our knowledge, this is the first case of CLL patient showing the nephrotic syndrome and acute renal failure caused by AL amyloidosis and neoplastic infiltration. Though AL amyloidosis caused by plasma cell dyscrasia usually responses poorly to chemotherapy, this patient exhibited a satisfactory clinical outcome due to successful inhibition of the production of amylodogenic light chains by combined chemotherapy