Searching for the scalar meson a0(1817)a_{0}(1817) in kaon induced reactions

In this study, we comprehensively investigate the production of isovector scalar meson $a_{0}(1817)$ using the effective Lagrangian approach. Specifically, we employ the Reggeized $t$-channel Born term to calculate the total and differential cross sections for the reaction $K^{-}p \rightarrow a_{0}(1817)\Lambda$. Our analysis reveals that the optimal energy range for detecting the $a_{0}(1817)$ meson lies between $W=3.4$ MeV and $W=3.6$ MeV, where the predicted total cross section reaches a minimum value of 112 nb. Notably, the $t$ channel, as predicted by the Regge model, significantly enhances the differential cross sections, particularly at extreme forward angles. Furthermore, we investigate the Dalitz processes of $2\rightarrow 3$ and discuss the feasibility of detecting the $a_{0}(1817)$ meson in experiments such as J-PARC.Comment: 6 pages, 6 figure

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Detection of gamma-ray emission from the Coma cluster with Fermi Large Area Telescope and tentative evidence for an extended spatial structure

Many galaxy clusters have giant halos of non-thermal radio emission, indicating the presence of relativistic electrons in the clusters. Relativistic protons may also be accelerated by merger and/or accretion shocks in galaxy clusters. These cosmic-ray (CR) electrons and/or protons are expected to produce gamma-rays through inverse-Compton scatterings or inelastic $pp$ collisions respectively. Despite of intense efforts in searching for high-energy gamma-ray emission from galaxy clusters, conclusive evidence is still missing so far. Here we report the discovery of $\ge 200$ MeV gamma-ray emission from the Coma cluster direction with an unbinned likelihood analysis of the 9 years of {\it Fermi}-LAT Pass 8 data. The gamma-ray emission shows a spatial morphology roughly coincident with the giant radio halo, with an apparent excess at the southwest of the cluster. Using the test statistic analysis, we further find tentative evidence that the gamma-ray emission at the Coma center is spatially extended. The extended component has an integral energy flux of $\sim 2\times 10^{-12}{\rm \ erg\ cm^{-2}\ s^{-1}}$ in the energy range of 0.2 - 300 GeV and the spectrum is soft with a photon index of $\simeq-2.7$. Interpreting the gamma-ray emission as arising from CR proton interaction, we find that the volume-averaged value of the CR to thermal pressure ratio in the Coma cluster is about $\sim 2\%$. Our results show that galaxy clusters are likely a new type of GeV gamma-ray sources, and they are probably also giant reservoirs of CR protons.Comment: 10 pages, 10 figures, Accepted by Physical Review D, more spatial models for the gamma-ray emission are used, systematic checks on the results are adde

Modelling of Capillary Pore Structure Evolution in Portland Cement Pastes Based on Irregular-Shaped Cement Particles

The pore structure plays a crucial role in durability performance of cement-based materials. However, the pore structure in cement pastes is highly dependent on the initial packing of cement particles and cement hydration process, which seems to be related to the shapes of cement particles. This paper proposed a numerical method to investigate the effect of cement particle shapes on capillary pore structures in cement pastes. In this study, irregular-shaped cement particles with various shapes are generated using a novel central growth model, and then incorporated into CEMHYD3D model to simulate Portland cement hydration. Some home-made programs of determining pore structure parameters including porosity, pore size distribution, connectivity and tortuosity are subsequently performed on the extracted three-dimensional network of capillary pore structure in cement pastes. The modelling results indicate that shape-induced large surface area in more non-equiaxed irregular-shaped cement particles can improve pore structure parameters in hardened cement pastes, but this effect will be slight in the later curing period and at a low water-tocement ratio. In addition, the less considered geometric difference plays a role in pore structure evolution especially for extremely non-equiaxed cement particle. However, the geometric attribute has a weak effect on pore structure parameters overall. The modelling results can provide a new insight into durability design in cement-based materials by means of manipulating cement particle shape in the future

CAMS: CAnonicalized Manipulation Spaces for Category-Level Functional Hand-Object Manipulation Synthesis

In this work, we focus on a novel task of category-level functional hand-object manipulation synthesis covering both rigid and articulated object categories. Given an object geometry, an initial human hand pose as well as a sparse control sequence of object poses, our goal is to generate a physically reasonable hand-object manipulation sequence that performs like human beings. To address such a challenge, we first design CAnonicalized Manipulation Spaces (CAMS), a two-level space hierarchy that canonicalizes the hand poses in an object-centric and contact-centric view. Benefiting from the representation capability of CAMS, we then present a two-stage framework for synthesizing human-like manipulation animations. Our framework achieves state-of-the-art performance for both rigid and articulated categories with impressive visual effects. Codes and video results can be found at our project homepage: https://cams-hoi.github.io/Comment: CVPR 2023 Receive

Photon orbits and phase transition for Non-Linear charged Anti-de Sitter black holes

In this work, we investigate the relationship between the photon sphere radius and the first-order phase transition for the charged EPYM AdS black hole. Through the analysis, we find with a certain condition there exist the non-monotonic behaviors between the photon sphere radius, the impact parameter, the non-linear YM charge parameter, temperature, and pressure. And both the changes of photon sphere radius and impact parameter before and after phase transition can be regarded as the order parameter, their critical exponents near the critical point are equal to the same value $1/2$, just like the ordinary thermal systems. These indicate that there maybe exists a universal relationship of gravity nearby the critical point for a black hole thermodynamical system. Furthermore, the effect of impact parameter on the deflect angle is also investigated

Masked Diffusion with Task-awareness for Procedure Planning in Instructional Videos

A key challenge with procedure planning in instructional videos lies in how to handle a large decision space consisting of a multitude of action types that belong to various tasks. To understand real-world video content, an AI agent must proficiently discern these action types (e.g., pour milk, pour water, open lid, close lid, etc.) based on brief visual observation. Moreover, it must adeptly capture the intricate semantic relation of the action types and task goals, along with the variable action sequences. Recently, notable progress has been made via the integration of diffusion models and visual representation learning to address the challenge. However, existing models employ rudimentary mechanisms to utilize task information to manage the decision space. To overcome this limitation, we introduce a simple yet effective enhancement - a masked diffusion model. The introduced mask acts akin to a task-oriented attention filter, enabling the diffusion/denoising process to concentrate on a subset of action types. Furthermore, to bolster the accuracy of task classification, we harness more potent visual representation learning techniques. In particular, we learn a joint visual-text embedding, where a text embedding is generated by prompting a pre-trained vision-language model to focus on human actions. We evaluate the method on three public datasets and achieve state-of-the-art performance on multiple metrics. Code is available at https://github.com/ffzzy840304/Masked-PDPP.Comment: 7 pages (main text excluding references), 3 figures, 7 table

Traditional Chinese medicine combined with hormone therapy to treat premature ovarian failure: a meta-analysis of randomized controlled trials

Background: This meta-analysis aimed to provide critically estimated evidence for the advantages and disadvantages of Chinese herbal medicines used for premature ovarian failure (POF), which could provide suggestions for rational treatments.Materials and Methods: The databases searched included MEDLINE, EMBASE, CNKI, VIP, China Dissertation Database, China Important Conference Papers Database, and online clinical trial registry websites. Published and unpublished randomized controlled trials of traditional Chinese medicine (TCM) combined with hormone therapy (HT) and HT alone for POF were assessed up to December 30, 2015. Two authors extracted data and assessed trial quality independently using Cochrane systematic review methods. Meta-analysis was used to quantitatively describe serum hormone levels and Kupperman scores associated with perimenopause symptoms.Results: Seventeen randomized controlled trials involving 1352 participants were selected. Compared with HT alone, although no significant effects were observed in the levels of luteinizing hormone, therapy with TCM combined with HT compared to HT alone effectively altered serum hormone levels of follicle stimulating hormone (P<0.01) and estradiol (P < 0.01), and improved Kupperman index scores (P< 0.01).Conclusions: The reported favorable effects of TCM combined with HT for treating POF patients are better than HT alone.However,the beneficial effects derived from this combination therapy cannot be viewed conclusive.In order to better support the clinical use, more rigorously designed trials are required to provide.Keywords: Traditional Chinese medicine, Hormone therapy, Premature ovarian failure, Meta-analysi

A Swarm-based Dynamic Evacuation Simulation Model Under the Background of Secondary Disasters

AbstractDue to the occurrence of secondary disasters in disaster relief, a swarm-based dynamic disaster evacuation simulation model is established to settle the practical difficulties of reducing efficiency in evacuation. And much better simulation results have been achieved than static plans or disorganized autonomous escape scheme. Simulation results show that “to changing the status quo” dynamic evacuation plan is much better than “maintaining the status quo,” the static and self-evacuation plan or autonomous escape behavior for emergency evacuation, especially those with secondary disasters