Numerical and experimental simulation of damaged rock with randomly oriented cracks by shock disturbance

The aim of this study is to investigate the effect of shock-disturbed cracks on the dynamic fragmentation of granite. Considering the complex behavior of rock materials, the Walsh’s model was revisited and extended by including the stress effect required to close an initially open crack and examining the unloading process in detail. This analysis leads to closed-form expressions for loading and unloading portions of the effective Young’s modulus, as functions of the crack density, characteristic aspect ratio, and crack friction coefficient. Subsequently, the effective Young’s modulus and cutting force are simulated and the influence of cracks is studied. The analysis results with different crack density and disturbed frequency are compared in terms of effective Young’s modulus and cutting force. Finally, the tool and damaged rock model with randomly oriented cracks by shock disturbed at a different frequency was demonstrated by the test. The good agreement between the simulation results and experimental data demonstrates the validity of the simulation method

Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality

Stochastic Gradient Descent (SGD) is one of the simplest and most popular algorithms in modern statistical and machine learning due to its computational and memory efficiency. Various averaging schemes have been proposed to accelerate the convergence of SGD in different settings. In this paper, we explore a general averaging scheme for SGD. Specifically, we establish the asymptotic normality of a broad range of weighted averaged SGD solutions and provide asymptotically valid online inference approaches. Furthermore, we propose an adaptive averaging scheme that exhibits both optimal statistical rate and favorable non-asymptotic convergence, drawing insights from the optimal weight for the linear model in terms of non-asymptotic mean squared error (MSE)

Product Complexity and Strategic Alliance on Drug Approval

Management of the business-government relationship is critical for firm performance in regulated industries. In this paper, we predict a U-shaped relationship between product complexity and the time to approval by the US Food and Drug Administration (FDA). Moreover, we argue that this association is contingent on the types of strategic alliances (i.e., R&D alliance, Marketing alliance) of the focal firm in that those alliances help FDA and pharmaceutical companies achieve harmony. Using the approved drugs by FDA from 1999 to 2016 as the sample, our hypotheses are supported by the empirical analysis on US pharmaceutical firms. The findings have important implications to achieving harmony between pharmaceutical firms and regulatory agencies

Product Complexity and Strategic Alliance on Drug Approval

Management of the business-government relationship is critical for firm performance in regulated industries. In this paper, we predict a U-shaped relationship between product complexity and the time to approval by the US Food and Drug Administration (FDA). Moreover, we argue that this association is contingent on the types of strategic alliances (i.e., R&D alliance, Marketing alliance) of the focal firm in that those alliances help FDA and pharmaceutical companies achieve harmony. Using the approved drugs by FDA from 1999 to 2016 as the sample, our hypotheses are supported by the empirical analysis on US pharmaceutical firms. The findings have important implications to achieving harmony between pharmaceutical firms and regulatory agencies

Daylight-driven rechargeable antibacterial and antiviral nanofibrous membranes for bioprotective applications.

Emerging infectious diseases (EIDs) are a significant burden on global economies and public health. Most present personal protective equipment used to prevent EID transmission and infections is typically devoid of antimicrobial activity. We report on green bioprotective nanofibrous membranes (RNMs) with rechargeable antibacterial and antiviral activities that can effectively produce biocidal reactive oxygen species (ROS) solely driven by the daylight. The premise of the design is that the photoactive RNMs can store the biocidal activity under light irradiation and readily release ROS under dim light or dark conditions, making the biocidal function "always online." The resulting RNMs exhibit integrated properties of fast ROS production, ease of activity storing, long-term durability, robust breathability, interception of fine particles (>99%), and high bactericidal (>99.9999%) and virucidal (>99.999%) efficacy, which enabled to serve as a scalable biocidal layer for protective equipment by providing contact killing against pathogens either in aerosol or in liquid forms. The successful synthesis of these fascinating materials may provide new insights into the development of protection materials in a sustainable, self-recharging, and structurally adaptive form

High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization

Uncertainty quantification for estimation through stochastic optimization solutions in an online setting has gained popularity recently. This paper introduces a novel inference method focused on constructing confidence intervals with efficient computation and fast convergence to the nominal level. Specifically, we propose to use a small number of independent multi-runs to acquire distribution information and construct a t-based confidence interval. Our method requires minimal additional computation and memory beyond the standard updating of estimates, making the inference process almost cost-free. We provide a rigorous theoretical guarantee for the confidence interval, demonstrating that the coverage is approximately exact with an explicit convergence rate and allowing for high confidence level inference. In particular, a new Gaussian approximation result is developed for the online estimators to characterize the coverage properties of our confidence intervals in terms of relative errors. Additionally, our method also allows for leveraging parallel computing to further accelerate calculations using multiple cores. It is easy to implement and can be integrated with existing stochastic algorithms without the need for complicated modifications

Global well-posedness for a class of 2D Boussinesq systems with fractional dissipation

Abstract The incompressible Boussinesq equations not only have many applications in modeling fluids and geophysical fluids but also are mathematically important. The well-posedness and related problem on the Boussinesq equations have recently attracted considerable interest. This paper examines the global regularity issue on the 2D Boussinesq equations with fractional Laplacian dissipation and thermal diffusion. Attention is focused on the case when the thermal diffusion dominates. We establish the global wellposedness for the 2D Boussinesq equations with a new range of fractional powers of the Laplacian

Product Complexity and Strategic Alliance on Drug Approval

Management of the business-government relationship is critical for firm performance in regulated industries. In this paper, we predict a U-shaped relationship between product complexity and the time to approval by the US Food and Drug Administration (FDA). Moreover, we argue that this association is contingent on the types of strategic alliances (i.e., R&D alliance, Marketing alliance) of the focal firm in that those alliances help FDA and pharmaceutical companies achieve harmony. Using the approved drugs by FDA from 1999 to 2016 as the sample, our hypotheses are supported by the empirical analysis on US pharmaceutical firms. The findings have important implications to achieving harmony between pharmaceutical firms and regulatory agencies

Implementation of TCP/NC protocol simulation based on OMNET++

Abstract-TCP protocol has an awful performance in the wireless network because of the instability, high BER and long RTT of the wireless link. How to make wireless transmission more reliable and efficient has become a hot topic among relative researches. TCP/NC is a recently proposed protocol based on network coding and capable of achieving much higher throughput than TCP over lossy wireless Links. In this paper, network coding and TCP/NC are outlined firstly. And then simulation realization of TCP/NC protocol in OMNET++ is described. The performance evaluation of TCP/NC is conducted in OMNET++. The results show that TCP/NC offers significant better performance than TCP without affecting the fairness of data flow