Component-based Analysis of Dynamic Search Performance

In many search scenarios, such as exploratory, comparative, or survey-oriented search, users interact with dynamic search systems to satisfy multi-aspect information needs. These systems utilize different dynamic approaches that exploit various user feedback granularity types. Although studies have provided insights about the role of many components of these systems, they used black-box and isolated experimental setups. Therefore, the effects of these components or their interactions are still not well understood. We address this by following a methodology based on Analysis of Variance (ANOVA). We built a Grid Of Points that consists of systems based on different ways to instantiate three components: initial rankers, dynamic rerankers, and user feedback granularity. Using evaluation scores based on the TREC Dynamic Domain collections, we built several ANOVA models to estimate the effects. We found that (i) although all components significantly affect search effectiveness, the initial ranker has the largest effective size, (ii) the effect sizes of these components vary based on the length of the search session and the used effectiveness metric, and (iii) initial rankers and dynamic rerankers have more prominent effects than user feedback granularity. To improve effectiveness, we recommend improving the quality of initial rankers and dynamic rerankers. This does not require eliciting detailed user feedback, which might be expensive or invasive.

Analysis of Thermal Performances in a Ventilated Room Using LBM-MRT: Effect of a Porous Separation

This article demonstrates the feasibility of porous separation on the performance of displacement ventilation in a rectangular enclosure. A jet of fresh air enters the cavity through an opening at the bottom of the left wall and exits through an opening at the top of the right wall. The porous separation is placed in the center of the cavity and its height varies between 0.2 and 0.8 with three values of thickness, 0.1, 0.2, and 0.3. The heat transfer rate was calculated for different intervals of Darcy (10−6 ≤ Da ≤ 10), Rayleigh (10 ≤ Ra ≤ 106), and Reynolds (50 ≤ Re ≤ 500) numbers. The momentum and the energy equations were solved by the lattice Boltzmann method with multiple relaxation times (LB-MRT). Schemes D2Q9 and D2Q5 were chosen for the velocity and temperature fields, respectively. For porous separation, the generalized Darcy–Brinkman–Forchheimer model was adopted. It is represented by a term added in the standard LB equations. For the dynamic domain, numerical simulations revealed complex flow structures depending on all control parameters. The results showed that the thermal field, mainly in the second compartment, is very dependent on the size and permeability of the porous separation. However, they have no influence on the transfer rate.

Strain rate sensitivity of ultra-high performance fiber reinforced concrete

Ultra High Performance Fiber Reinforced Concrete (UHP-FRC) is relatively new cementitious material, which has been developed to enhance material performance such as, durability, workability and strength. UHP-FRC has an outstanding dynamic performance with high capacity to absorb damage. Because of its superior performance under dynamic loading, UHP-FRC has been induced in structures where dynamic resistance is required. It is proven that like other concrete materials, UHP-FRC strength increases significantly when subjected to high strain rates. The objective of this study is to develop understanding of strain rate sensitivity of UHP-FRC with 2% steel fiber by volume fraction and plain High Strength Concrete (HSC). Compressive and flexural tensile strength of each concrete composite were investigated to evaluate and compare their strain rate sensitivity through dynamic increase factor (DIF). The specimens were tested under six different strain rates; three in quasi-static and three in dynamic domain. Strain rates in quasi-static domain conducted by MTS test machine and strain rates in dynamic domain conducted using the drop hammer technique. The test results revealed that UHP-FRC exhibits less strain rate sensitivity while HSC show much higher rate sensitivity in comparison to other materials.

Strain rate sensitivity of ultra-high performance fiber reinforced concrete

Ultra High Performance Fiber Reinforced Concrete (UHP-FRC) is relatively new cementitious material, which has been developed to enhance material performance such as, durability, workability and strength. UHP-FRC has an outstanding dynamic performance with high capacity to absorb damage. Because of its superior performance under dynamic loading, UHP-FRC has been induced in structures where dynamic resistance is required. It is proven that like other concrete materials, UHP-FRC strength increases significantly when subjected to high strain rates. The objective of this study is to develop understanding of strain rate sensitivity of UHP-FRC with 2% steel fiber by volume fraction and plain High Strength Concrete (HSC). Compressive and flexural tensile strength of each concrete composite were investigated to evaluate and compare their strain rate sensitivity through dynamic increase factor (DIF). The specimens were tested under six different strain rates; three in quasi-static and three in dynamic domain. Strain rates in quasi-static domain conducted by MTS test machine and strain rates in dynamic domain conducted using the drop hammer technique. The test results revealed that UHP-FRC exhibits less strain rate sensitivity while HSC show much higher rate sensitivity in comparison to other materials.

Detecting Multielement Algorithmically Generated Domain Names Based on Adaptive Embedding Model

With the development of detection algorithms on malicious dynamic domain names, domain generation algorithms have developed to be more stealthy. The use of multiple elements for generating domains will lead to higher detection difficulty. To effectively improve the detection accuracy of algorithmically generated domain names based on multiple elements, a domain name syntax model is proposed, which analyzes the multiple elements in domain names and their syntactic relationship, and an adaptive embedding method is proposed to achieve effective element parsing of domain names. A parallel convolutional model based on the feature selection module combined with an improved dynamic loss function based on curriculum learning is proposed, which can achieve effective detection on multielement malicious domain names. A series of experiments are designed and the proposed model is compared with five previous algorithms. The experimental results denote that the detection accuracy of the proposed model for multiple-element malicious domain names is significantly higher than that of the comparison algorithms and also has good adaptability to other types of malicious domain names.

Mutation in a SARS-CoV-2 Haplotype from Sub-Antarctic Chile Reveals New Insights into the Spike’s Dynamics

The emergence of SARS-CoV-2 variants, as observed with the D614G spike protein mutant and, more recently, with B.1.1.7 (501Y.V1), B.1.351 (501Y.V2) and B.1.1.28.1 (P.1) lineages, represent a continuous threat and might lead to strains of higher infectivity and/or virulence. We report on the occurrence of a SARS-CoV-2 haplotype with nine mutations including D614G/T307I double-mutation of the spike. This variant expanded and completely replaced previous lineages within a short period in the subantarctic Magallanes Region, southern Chile. The rapid lineage shift was accompanied by a significant increase of cases, resulting in one of the highest incidence rates worldwide. Comparative coarse-grained molecular dynamic simulations indicated that T307I and D614G belong to a previously unrecognized dynamic domain, interfering with the mobility of the receptor binding domain of the spike. The T307I mutation showed a synergistic effect with the D614G. Continuous surveillance of new mutations and molecular analyses of such variations are important tools to understand the molecular mechanisms defining infectivity and virulence of current and future SARS-CoV-2 strains.