Does reduced usage of antibiotics in livestock production mitigate the spread of antibiotic resistance in soil, earthworm guts, and the phyllosphere?

The overuse of antibiotics in animal husbandry is widespread and believed to significantly contribute to the selection of antibiotic resistance genes (ARGs) in animals. Thus, there is a global drive to reduce antibiotic use in the agricultural sector. However, it has not been established whether a reduction in the use of antibiotics in livestock production would be effective in reducing the spread of ARGs. A microcosm approach was used to determine how the addition of manure with either reduced antibiotic levels or with typical antibiotic levels could affect the spread of antibiotic resistance genes between soil, earthworms and the phyllosphere. When compared to the control soil, earthworm and phyllosphere samples had the greater increase in ARG abundance in conventional manure treatments (P < 0.05). Reduced antibiotic manure also enriched the abundance of ARGs in the phyllosphere and soil but not earthworm guts when compared to the control (P < 0.05). In both soil and earthworm guts, the enrichment of ARGs was lower in reduced antibiotic manure than in conventional manure. This study has identified bacterial transfer through the soil-earthworm-phyllosphere system as a potential means to spread ARGs between habitats after fertilization with livestock derived manures

Quasinormal Modes of C-metric from SCFTs

We study the quasinormal modes (QNM) of the charged C-metric, which physically stands for a charged accelerating black hole, with the help of Nekrasov's partition function of 4d $\mathcal{N}=2$ superconformal field theories (SCFTs). The QNM in the charged C-metric are classified into three types: the photon-surface modes, the accelerating modes and the near-extremal modes, and it is curious how the single quantization condition proposed in arXiv:2006.06111 can reproduce all the different families. We show that the connection formula encoded in terms of Nekrasov's partition function captures all these families of QNM numerically and recovers the asymptotic behavior of the accelerating and the near-extremal modes analytically. Using the connection formulae of different 4d $\mathcal{N}=2$ SCFTs, one can solve both the radial and the angular part of the scalar perturbation equation respectively. The same algorithm can be applied to the de Sitter (dS) black holes to calculate both the dS modes and the photon-sphere modes.Comment: 46+8 page

A multi-objective optimization scheduling method based on the ant colony algorithm in cloud computing

Abstract: For task-scheduling problems in cloud computing, a multi-objective optimization method is proposed here. First, with an aim toward the biodiversity of resources and tasks in cloud computing, we propose a resource cost model that defines the demand of tasks on resources with more details. This model reflects the relationship between the user's resource costs and the budget costs. A multi-objective optimization scheduling method has been proposed based on this resource cost model. This method considers the makespan and the user's budget costs as constraints of the optimization problem, achieving multi-objective optimization of both performance and cost. An improved ant colony algorithm has been proposed to solve this problem. Two constraint functions were used to evaluate and provide feedback regarding the performance and budget cost. These two constraint functions made the algorithm adjust the quality of the solution in a timely manner based on feedback in order to achieve the optimal solution. Some simulation experiments were designed to evaluate this method's performance using four metrics: 1) the makespan; 2) cost; 3) deadline violation rate; and 4) resource utilization. Experimental results show that based on these four metrics, a multi-objective optimization method is better than other similar methods, especially as it increased 56.6% in the best case scenario

Optical loss compensation in a bulk left-handed metamaterial by the gain in quantum dots

A bulk left-handed metamaterial with fishnet structure is investigated to show the optical loss compensation via surface plasmon amplification, with the assistance of a Gaussian gain in PbS quantum dots. The optical resonance enhancement around 200 THz is confirmed by the retrieval method. By exploring the dependence of propagation loss on the gain coefficient and metamaterial thickness, we verify numerically that the left-handed response can endure a large propagation thickness with ultralow and stable loss under a certain gain coefficient.Comment: 6 pages with 4 figure

A multiqueue interlacing peak scheduling method based on tasks’ classification in cloud computing

In cloud computing, resources are dynamic, and the demands placed on the resources allocated to a particular task are diverse. These factors could lead to load imbalances, which affect scheduling efficiency and resource utilization. A scheduling method called interlacing peak is proposed. First, the resource load information, such as CPU, I/O, and memory usage, is periodically collected and updated, and the task information regarding CPU, I/O, and memory is collected. Second, resources are sorted into three queues according to the loads of the CPU, I/O, and memory: CPU intensive, I/O intensive, and memory intensive, according to their demands for resources. Finally, once the tasks have been scheduled, they need to interlace the resource load peak. Some types of tasks need to be matched with the resources whose loads correspond to a lighter types of tasks. In other words, CPU-intensive tasks should be matched with resources with low CPU utilization; I/O-intensive tasks should be matched with resources with shorter I/O wait times; and memory-intensive tasks should be matched with resources that have low memory usage. The effectiveness of this method is proved from the theoretical point of view. It has also been proven to be less complex in regard to time and place. Four experiments were designed to verify the performance of this method. Experiments leverage four metrics: 1) average response time; 2) load balancing; 3) deadline violation rates; and 4) resource utilization. The experimental results show that this method can balance loads and improve the effects of resource allocation and utilization effectively. This is especially true when resources are limited. In this way, many tasks will compete for the same resources. However, this method shows advantage over other similar standard algorithms

The extended BLMSSM with a 125 GeV Higgs boson and dark matter

To extend the BLMSSM, we not only add exotic Higgs superfields $(\Phi_{NL},\varphi_{NL})$ to make the exotic lepton heavy, but also introduce the superfields($Y$,$Y^\prime$) having couplings with lepton and exotic lepton at tree level. The obtained model is called as EBLMSSM, which has difference from BLMSSM especially for the exotic slepton(lepton) and exotic sneutrino(neutrino). We deduce the mass matrices and the needed couplings in this model. To confine the parameter space, the Higgs boson mass $m_{h^0}$ and the processes $h^0\rightarrow \gamma\gamma$, $h^0\rightarrow VV, V=(Z,W)$ are studied in the EBLMSSM. With the assumed parameter space, we obtain reasonable numerical results according to data on Higgs from ATLAS and CMS. As a cold dark mater candidate, the relic density for the lightest mass eigenstate of $Y$ and $Y'$ mixing is also studied

Prediction of large esophageal varices in cirrhotic patients using classification and regression tree analysis

OBJECTIVES: Recent guidelines recommend that all cirrhotic patients should undergo endoscopic screening for esophageal varices. That identifying cirrhotic patients with esophageal varices by noninvasive predictors would allow for the restriction of the performance of endoscopy to patients with a high risk of having varices. This study aimed to develop a decision model based on classification and regression tree analysis for the prediction of large esophageal varices in cirrhotic patients. METHODS: 309 cirrhotic patients (training sample, 187 patients; test sample 122 patients) were included. Within the training sample, the classification and regression tree analysis was used to identify predictors and prediction model of large esophageal varices. The prediction model was then further evaluated in the test sample and different Child-Pugh classes. RESULTS: The prevalence of large esophageal varices in cirrhotic patients was 50.8%. A tree model that was consisted of spleen width, portal vein diameter and prothrombin time was developed by classification and regression tree analysis achieved a diagnostic accuracy of 84% for prediction of large esophageal varices. When reconstructed into two groups, the rate of varices was 83.2% for high-risk group and 15.2% for low-risk group. Accuracy of the tree model was maintained in the test sample and different Child-Pugh classes. CONCLUSIONS: A decision tree model that consists of spleen width, portal vein diameter and prothrombin time may be useful for prediction of large esophageal varices in cirrhotic patient

Resonance amplification of left-handed transmission at optical frequencies by stimulated emission of radiation in active metamaterials

We demonstrate that left-handed resonance transmission from metallic metamaterial, composed of periodically arranged double rings, can be extended to visible spectrum by introducing an active medium layer as the substrate. The severe ohmic loss inside metals at optical frequencies is compensated by stimulated emission of radiation in this active system. Due to the resonance amplification mechanism of recently proposed lasing spaser, the left-handed transmission band can be restored up to 610 nm wavelength, in dependence on the gain coefficient of the active layer. Additionally, threshold gains for different scaling levels of the double-ring unit are investigated to evaluate the gain requirement of left-handed transmission restoration at different frequency ranges.Comment: 12 pages, 5 figure

Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations; 2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features; 3) Camera-LiDAR fusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models.Comment: 8 pages, CVPR202

Light neutralino dark matter in U(1)XU(1)_XSSM

The $U(1)_X$ extension of the minimal supersymmetric standard model(MSSM) is called as $U(1)_X$SSM with the local gauge group $SU(3)_C\times SU(2)_L \times U(1)_Y \times U(1)_X$. $U(1)_X$SSM has three singlet Higgs superfields beyond MSSM. In $U(1)_X$SSM, the mass matrix of neutralino is $8\times8$, whose lightest mass eigenstate possesses cold dark matter characteristic. Supposing the lightest neutralino as dark matter candidate, we study the relic density. For dark matter scattering off nucleus, the cross sections including spin-independent and spin-dependent are both researched. In our numerical results, some parameter space can satisfy the constraints from the relic density and the experiments of dark matter direct detection.Comment: 23 pages, 9 figure