Simulation Experiment Research for Exploding in Fracture

On the basis of low permeability exploiting statement, “Exploding in fracture” is present in this paper and the feasibility and safety of this technology is also analyzed. It is found that the rock damage and fracture by shock wave in “Exploding in Fracture” can be simulated by the experiment of exploding on the surface of the cement sample in deep water. The damage and fracture of the cement sample, and the wave propagation proceed, and the damage and fracture mechanism are described qualitatively. It is found that the micro-fractures and compacted wave have an intimate relationship with the initial damage of the sample. The numerical simulation result is accordant with the experiment result. It also concluded that the qualitative explanation of rock damage and fracture mechanism is right. The compacted damage zone has definite permeability, which has an important means to “Exploding in Fracture” technology.Key words: Simulation experiment; Exploding in fracture; Damage and fractur

Te Test: A New Non-asymptotic T-test for Behrens-Fisher Problems

The Behrens-Fisher Problem is a classical statistical problem. It is to test the equality of the means of two normal populations using two independent samples, when the equality of the population variances is unknown. Linnik (1968) has shown that this problem has no exact fixed-level tests based on the complete sufficient statistics. However, exact conventional solutions based on other statistics and approximate solutions based the complete sufficient statistics do exist. Existing methods are mainly asymptotic tests, and usually don't perform well when the variances or sample sizes differ a lot. In this paper, we propose a new method to find an exact t-test (Te) to solve this classical Behrens-Fisher Problem. Confidence intervals for the difference between two means are provided. We also use detailed analysis to show that Te test reaches the maximum of degree of freedom and to give a weak version of proof that Te test has the shortest confidence interval length expectation. Some simulations are performed to show the advantages of our new proposed method compared to available conventional methods like Welch's test, paired t-test and so on. We will also compare it to unconventional method, like two-stage test.Comment: 27 page

Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor.

Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato leaves in different stages, including early or asymptomatic stages. One healthy leaf and three diseased tomato leaves (late blight, target and bacterial spots) were defined into four stages (healthy, asymptomatic, early stage and late stage) and collected from a field. Fifty-seven spectral vegetation indices (SVIs) were calculated in accordance with methods published in previous studies and established in this study. Principal component analysis was conducted to evaluate SVIs. Results revealed six principal components (PCs) whose eigenvalues were greater than 1. SVIs with weight coefficients ranking from 1 to 30 in each selected PC were applied to a K-nearest neighbour for classification. Amongst the examined leaves, the healthy ones had the highest accuracy (100%) and the lowest error rate (0) because of their uniform tissues. Late stage leaves could be distinguished more easily than the two other disease categories caused by similar symptoms on the multi-diseased leaves. Further work may incorporate the proposed technique into an image system that can be operated to monitor multi-diseased tomato plants in fields

Experimental and Numerical Analysis of Rock Burst Tendency and Crack Development Characteristics of Tianhu Granite

Rock burst is a serious nonlinear dynamic geological hazard in underground engineering construction. In this paper, a true triaxial unloading rock burst experiment and numerical simulation are carried out on Tianhu granite to investigate the rock burst tendency and crack development characteristics of surrounding rock after excavation. The experiment and numerical simulation process monitored the rock burst stress path to determine the rock burst stress. According to the evolution law of the frequency and amplitude of rock burst acoustic emission monitoring, the shape characteristics of rock burst fragments are analyzed. The rock burst numerical simulation analysis is carried out by the PFC software, and the temporal and spatial evolution law of cracks is obtained. The research results show that the laboratory experiment and numerical simulation of Tianhu granite have rock burst strengths of 163.4 MPa and 161 MPa, respectively, and the average rock burst stress ratio is 8.38, that is, the Tianhu granite has a low rock burst tendency. During the rock burst, the development of tensile cracks will produce flaky debris, and the development of shear cracks will produce lumpy debris. Rock burst will happen when the crack growth rate to be exceeded the unloading crack growth rate; therefore, it can be used as a precursor signal for the occurrence of rock burst

Probe-based end-to-end overload control for networks of SIP servers

The Session Initiation Protocol (SIP) has been adopted by the IETF as the control protocol for creating, modifying and terminating multimedia sessions. Overload occurs in SIP networks when SIP servers have insufficient resources to handle received messages. Under overload, SIP networks may suffer from congestion collapse due to current ineffective SIP overload control mechanisms. This paper introduces a probe-based end-to-end overload control (PEOC) mechanism, which is deployed at the edge servers of SIP networks and is easy to implement. By probing the SIP network with SIP messages, PEOC estimates the network load and controls the traffic admitted to the network according to the estimated load. Theoretic analysis and extensive simulations verify that PEOC can keep high throughput for SIP networks even when the offered load exceeds the capacity of the network. Besides, it can respond quickly to the sudden variations of the offered load and achieve good fairness

A feature preserved mesh simplification algorithm

Large-volume mesh model faces challenge in rendering, storing, and transmission due to large size of polygon data. Mesh simplification is one of solutions to reduce the data size. This paper presents a mesh simplification method based on feature extraction with curvature estimation to triangle mesh. The simplified topology preserves good geometrical features in the area with distinct features, that is, coarse simplified mesh in the flat region and fine simplified mesh around the areas of crease and corner. Sequence of mesh simplification is controlled on the basis of geometrical feature sensitivity, which results in reasonable simplification topology with less data size. This algorithm can decrease the size of the file by largely simplifying flat areas and preserving the geometric feature as well

UBXN3B Positively Regulates STING-Mediated Antiviral Immune Responses

The ubiquitin regulatory X domain-containing proteins (UBXNs) are likely involved in diverse biological processes. Their physiological functions, however, remain largely unknown. Here we present physiological evidence that UBXN3B positively regulates stimulator-of-interferon genes (STING) signaling. We employ a tamoxifen-inducible Cre-LoxP approach to generate systemic Ubxn3b knockout in adult mice as the Ubxn3b-null mutation is embryonically lethal. Ubxn3b(-/-), like Sting(-/-) mice, are highly susceptible to lethal herpes simplex virus 1 (HSV-1) and vesicular stomatitis virus (VSV) infection, which is correlated with deficient immune responses when compared to Ubxn3b(+/+) littermates. HSV-1 and STING agonist-induced immune responses are also reduced in several mouse and human Ubxn3b(-/-) primary cells. Mechanistic studies demonstrate that UBXN3B interacts with both STING and its E3 ligase TRIM56, and facilitates STING ubiquitination, dimerization, trafficking, and consequent recruitment and phosphorylation of TBK1. These results provide physiological evidence that links the UBXN family with antiviral immune responses

Detection of multi-tomato leaf diseases (\u3ci\u3elate blight, target and bacterial spots\u3c/i\u3e) in different stages by using a spectral-based sensor

Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato leaves in different stages, including early or asymptomatic stages. One healthy leaf and three diseased tomato leaves (late blight, target and bacterial spots) were defined into four stages (healthy, asymptomatic, early stage and late stage) and collected from a field. Fifty-seven spectral vegetation indices (SVIs) were calculated in accordance with methods published in previous studies and established in this study. Principal component analysis was conducted to evaluate SVIs. Results revealed six principal components (PCs) whose eigenvalues were greater than 1. SVIs with weight coefficients ranking from 1 to 30 in each selected PC were applied to a K-nearest neighbor for classification. Amongst the examined leaves, the healthy ones had the highest accuracy (100%) and the lowest error rate (0) because of their uniform tissues. Late stage leaves could be distinguished more easily than the two other disease categories caused by similar symptoms on the multi-diseased leaves. Further work may incorporate the proposed technique into an image system that can be operated to monitor multi-diseased tomato plants in fields

Zika Virus Non-structural Protein 4A Blocks the RLR-MAVS Signaling

Flaviviruses have evolved complex mechanisms to evade the mammalian host immune systems including the RIG-I (retinoic acid-inducible gene I) like receptor (RLR) signaling. Zika virus (ZIKV) is a re-emerging flavivirus that is associated with severe neonatal microcephaly and adult Guillain-Barre syndrome. However, the molecular mechanisms underlying ZIKV pathogenesis remain poorly defined. Here we report that ZIKV non-structural protein 4A (NS4A) impairs the RLR-mitochondrial antiviral-signaling protein (MAVS) interaction and subsequent induction of antiviral immune responses. In human trophoblasts, both RIG-I and melanoma differentiation-associated protein 5 (MDA5) contribute to type I interferon (IFN) induction and control ZIKV replication. Type I IFN induction by ZIKV is almost completely abolished in MAVS(-/-) cells. NS4A represses RLR-, but not Toll-like receptor-mediated immune responses. NS4A specifically binds the N-terminal caspase activation and recruitment domain (CARD) of MAVS and thus blocks its accessibility by RLRs. Our study provides in-depth understanding of the molecular mechanisms of immune evasion by ZIKV and its pathogenesis

S3: Social-network Simulation System with Large Language Model-Empowered Agents

Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanation, and policy-making support, among others. In this work, we harness the formidable human-like capabilities exhibited by large language models (LLMs) in sensing, reasoning, and behaving, and utilize these qualities to construct the S$^3$ system (short for $\textbf{S}$ocial network $\textbf{S}$imulation $\textbf{S}$ystem). Adhering to the widely employed agent-based simulation paradigm, we employ prompt engineering and prompt tuning techniques to ensure that the agent's behavior closely emulates that of a genuine human within the social network. Specifically, we simulate three pivotal aspects: emotion, attitude, and interaction behaviors. By endowing the agent in the system with the ability to perceive the informational environment and emulate human actions, we observe the emergence of population-level phenomena, including the propagation of information, attitudes, and emotions. We conduct an evaluation encompassing two levels of simulation, employing real-world social network data. Encouragingly, the results demonstrate promising accuracy. This work represents an initial step in the realm of social network simulation empowered by LLM-based agents. We anticipate that our endeavors will serve as a source of inspiration for the development of simulation systems within, but not limited to, social science