Features and stability analysis of non-Schwarzschild black hole in quadratic gravity

Black holes are found to exist in gravitational theories with the presence of quadratic curvature terms and behave differently from the Schwarzschild solution. We present an exhaustive analysis for determining the quasinormal modes of a test scalar field propagating in a new class of black hole backgrounds in the case of pure Einstein-Weyl gravity. Our result shows that the field decay of quasinormal modes in such a non-Schwarzschild black hole behaves similarly to the Schwarzschild one, but the decay slope becomes much smoother due to the appearance of the Weyl tensor square in the background theory. We also analyze the frequencies of the quasinormal modes in order to characterize the properties of new back holes, and thus, if these modes can be the source of gravitational waves, the underlying theories may be testable in future gravitational wave experiments. We briefly comment on the issue of quantum (in)stability in this theory at linear order.Comment: 18 pages, 4 figures, 1 table, several references added, version published on JHE

EDDA: An Efficient Distributed Data Replication Algorithm in VANETs

Efficient data dissemination in vehicular ad hoc networks (VANETs) is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA). The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to speed up the dissemination process. We calculate the number of communication stages for the network to enter into a balanced status and show that the proposed distributed algorithm can converge to a consensus in a small number of communication stages. Most of the theoretical results described in this paper are to study the complexity of network convergence. The lower bound and upper bound are also provided in the analysis of the algorithm. Simulation results show that the proposed EDDA can efficiently disseminate messages to vehicles in a specific area with low dissemination delay and system overhead

Dual-Channel Multiplex Graph Neural Networks for Recommendation

Efficient recommender systems play a crucial role in accurately capturing user and item attributes that mirror individual preferences. Some existing recommendation techniques have started to shift their focus towards modeling various types of interaction relations between users and items in real-world recommendation scenarios, such as clicks, marking favorites, and purchases on online shopping platforms. Nevertheless, these approaches still grapple with two significant shortcomings: (1) Insufficient modeling and exploitation of the impact of various behavior patterns formed by multiplex relations between users and items on representation learning, and (2) ignoring the effect of different relations in the behavior patterns on the target relation in recommender system scenarios. In this study, we introduce a novel recommendation framework, Dual-Channel Multiplex Graph Neural Network (DCMGNN), which addresses the aforementioned challenges. It incorporates an explicit behavior pattern representation learner to capture the behavior patterns composed of multiplex user-item interaction relations, and includes a relation chain representation learning and a relation chain-aware encoder to discover the impact of various auxiliary relations on the target relation, the dependencies between different relations, and mine the appropriate order of relations in a behavior pattern. Extensive experiments on three real-world datasets demonstrate that our \model surpasses various state-of-the-art recommendation methods. It outperforms the best baselines by 10.06\% and 12.15\% on average across all datasets in terms of R@10 and N@10 respectively

Biochemical mechanisms preventing wilting under grafting: a case study on pumpkin rootstock grafting to wax gourd

Wax gourd wilt is a devastating fungal disease caused by a specialized form of Fusarium oxysporum Schl. f. sp. benincasae (FOB), which severely restricts the development of the wax gourd industry. Resistant rootstock pumpkin grafting is often used to prevent and control wax gourd wilt. The “Haizhan 1” pumpkin has the characteristic of high resistance to wilt, but the mechanism through which grafted pumpkin rootstock plants acquire resistance to wax gourd wilt is still poorly understood. In this study, grafted wax gourd (GW) and self-grafted wax gourd (SW) were cultured at three concentrations [2.8 × 106 Colony Forming Units (CFU)·g−1, 8.0 × 105 CFU·g−1, and 4.0 × 105 CFU·g−1, expressed by H, M, and L]. Three culture times (6 dpi, 10 dpi, and 13 dpi) were used to observe the incidence of wilt disease in the wax gourd and the number of F. oxysporum spores in different parts of the soil and plants. Moreover, the physiological indices of the roots of plants at 5 dpi, 9 dpi, and 12 dpi in soil supplemented with M (8.0 × 105 CFU·g−1) were determined. No wilt symptoms in GW. Wilt symptoms in SW were exacerbated by the amount of FOB in the inoculated soil and culture time. At any culture time, the amount of FOB in the GW soil under the three treatments was greater than that in the roots. However, for the SW treatments, at 10 dpi and 13 dpi, the amount of FOB in the soil was lower than that in the roots. The total phenol (TP) and lignin (LIG) contents and polyphenol oxidase (PPO) and chitinase (CHI) activities were significantly increased in the GWM roots. The activities of phenylalanine ammonia lyase (PAL) and peroxidase (POD) initially decreased but then increased in the GWM roots. When the TP content decreased significantly, the LIG content and PAL and CHI activities increased initially but then decreased, whereas the PPO and POD activities did not change significantly in the SWM roots. The results indicated that the roots of the “Haizhan 1” pumpkin stock plants initiated a self-defense response after being infected with FOB, and the activities of PPO, POD, PAL, and CHI increased, and additional LIG and TP accumulated, which could effectively prevent FOB infection

Tracing primordial black holes in nonsingular bouncing cosmology

We in this paper investigate the formation and evolution of primordial black holes (PBHs) in nonsingular bouncing cosmologies. We discuss the formation of PBH in the contracting phase and calculate the PBH abundance as a function of the sound speed and Hubble parameter. Afterwards, by taking into account the subsequent PBH evolution during the bouncing phase, we derive the density of PBHs and their Hawking radiation. Our analysis shows that nonsingular bounce models can be constrained from the backreaction of PBHs

Learning Structure-Guided Diffusion Model for 2D Human Pose Estimation

One of the mainstream schemes for 2D human pose estimation (HPE) is learning keypoints heatmaps by a neural network. Existing methods typically improve the quality of heatmaps by customized architectures, such as high-resolution representation and vision Transformers. In this paper, we propose \textbf{DiffusionPose}, a new scheme that formulates 2D HPE as a keypoints heatmaps generation problem from noised heatmaps. During training, the keypoints are diffused to random distribution by adding noises and the diffusion model learns to recover ground-truth heatmaps from noised heatmaps with respect to conditions constructed by image feature. During inference, the diffusion model generates heatmaps from initialized heatmaps in a progressive denoising way. Moreover, we further explore improving the performance of DiffusionPose with conditions from human structural information. Extensive experiments show the prowess of our DiffusionPose, with improvements of 1.6, 1.2, and 1.2 mAP on widely-used COCO, CrowdPose, and AI Challenge datasets, respectively

Optimal dosage ranges of various exercise types for enhancing timed up and go performance in Parkinson’s disease patients: a systematic review and Bayesian network meta-analysis

ObjectiveTo examine the dose–response relationship between specific types of exercise for alleviating Timed up and Go (TUG) in Parkinson’s disease PD.DesignSystematic review and Bayesian network meta-analysis.Data sourcesPubMed, Medline, Embase, PsycINFO, Cochrane Library, and Web of Science were searched from inception until February 5th, 2024.Study analysisData analysis was conducted using R software with the MBNMA package. Effect sizes of outcome indicators were expressed as mean deviation (MD) and 95% confidence intervals (95% CrI). The risk of bias in the network was evaluated independently by two reviewers using ROB2.ResultsA total of 73 studies involving 3,354 PD patients. The text discusses dose–response relationships in improving TUG performance among PD patients across various exercise types. Notably, Aquatic (AQE), Mix Exercise (Mul_C), Sensory Exercise (SE), and Resistance Training (RT) demonstrate effective dose ranges, with AQE optimal at 1500 METs-min/week (MD: −8.359, 95% CI: −1.398 to −2.648), Mul_C at 1000 METs-min/week (MD: −4.551, 95% CI: −8.083 to −0.946), SE at 1200 METs-min/week (MD: −5.145, 95% CI: −9.643 to −0.472), and RT at 610 METs-min/week (MD: −2.187, 95% CI: −3.161 to −1.278), respectively. However, no effective doses are found for Aerobic Exercise (AE), Balance Gait Training (BGT), Dance, and Treadmill Training (TT). Mind–body exercise (MBE) shows promise with an effective range of 130 to 750 METs-min/week and an optimal dose of 750 METs-min/week (MD: −2.822, 95% CI: −4.604 to −0.996). According to the GRADE system, the included studies’ overall quality of the evidence was identified moderate level.ConclusionThis study identifies specific exercise modalities and dosages that significantly enhance TUG performance in PD patients. AQE emerges as the most effective modality, with an optimal dosage of 1,500 METs-min/week. MBE shows significant benefits at lower dosages, catering to patients with varying exercise capacities. RT exhibits a nuanced “U-shaped” dose–response relationship, suggesting an optimal range balancing efficacy and the risk of overtraining. These findings advocate for tailored exercise programs in PD management, emphasizing personalized prescriptions to maximize outcomes.Systematic Review Registration: International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024506968)

Aprendizaje colaborativo: Tutorías colaborativas y otras experiencias basadas en la cooperación y el apoyo mutuo entre estudiantes

Memoria del Proyecto de innovación Innova docencia de la convocatoria de 2019-20, consistente en la aplicación de una experiencia de aprendizaje colaborativo a partir de un sistema de tutorías colaborativas en 5 asignaturas de Grado de 4 facultades de la UCM. Asimismo, se realizó otra experiencia de trabajo colaborativo entre estudiantes y profesor en dos asignaturas del Máster Oficial en Comunicación Social de la UCM

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data