Motivated by the recent blockchain technology originally built for bitcoin transactions, various industries are exploring the opportunities to redefine their existing operational systems. In this ...study, an innovative environmentally sustainable solution is proposed for the fashion apparel manufacturing industry (FAMI), which is energized by blockchain. Incorporating the Emission Trading Scheme (ETS), and a novel “emission link” system, the proposed framework exposes carbon emission to the public and establishes a feature to reduce the emissions for all key steps of clothing making. Fully compatible with Industry 4.0, blockchain provides decentralization, transparency, automation, and immutability characteristics to the proposed framework. Specifically, the blockchain supported ETS framework, the carbon emissions of clothing manufacturing life cycle, and the emission link powered procedures are introduced in detail. A case study is provided to demonstrate the carbon emission evaluation procedure. Finally, a multi-criteria evaluation is performed to demonstrate the benefits and drawbacks of the proposed system.
In this article, the sliding-mode control (SMC) strategy is outlined for discrete-time singular Markovian jump systems with time-varying delays and time-varying transition probabilities (TPs). To ...simplify the complexities arising from the time-varying TPs in the Markov chain, the TPs in this study are reasonably considered to be finite piecewise-homogeneous. The variations of TPs are stochastic and governed by a higher level transition probability (HTP) matrix. It is acceptable for both the TP matrix and HTP matrix to be partly unknown, which makes the system closer to reality and more complex to investigate. In this context, our goal lies in constructing a common sliding-mode surface to avoid the effects of switching among sequential subsystems and piecewise homogeneous TPs on the convergence of the sliding-mode surface. Additionally, we aim to design an appropriate SMC law to guarantee the reachability of the quasi-sliding mode in a finite-time interval. Through the linear matrix inequalities, sufficient criteria are offered to make the closed-loop dynamic system stochastically admissible. Finally, the numerical result will show that the presented SMC strategy is valid.
The aspartate aminotransferase‐to‐platelet ratio index (APRI), a tool with limited expense and widespread availability, is a promising noninvasive alternative to liver biopsy for detecting hepatic ...fibrosis. The objective of this study was to update the 2007 meta‐analysis to systematically assess the accuracy of APRI in predicting significant fibrosis, severe fibrosis, and cirrhosis stage in hepatitis C virus (HCV) monoinfected and HCV / human immunodeficiency virus (HIV) coinfected individuals. Studies comparing APRI versus biopsy in HCV patients were identified via a thorough literature search. Areas under summary receiver operating characteristic curves (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to examine the APRI accuracy for the diagnosis of significant fibrosis, severe fibrosis, and cirrhosis. Heterogeneity was explored using meta‐regression. Twenty‐one additional studies were eligible for the update and, in total, 40 studies were included in this review (n = 8,739). The summary AUROC of the APRI for the diagnosis of significant fibrosis, severe fibrosis, and cirrhosis were 0.77, 0.80, and 0.83, respectively. For significant fibrosis, an APRI threshold of 0.7 was 77% sensitive and 72% specific. For severe fibrosis, a threshold of 1.0 was 61% sensitive and 64% specific. For cirrhosis, a threshold of 1.0 was 76% sensitive and 72% specific. Moreover, we found that the APRI was less accurate for the identification of significant fibrosis, severe fibrosis, and cirrhosis in HIV/HCV coinfected patients. Conclusion: Our large meta‐analysis suggests that APRI can identify hepatitis C‐related fibrosis with a moderate degree of accuracy. Application of this index may decrease the need for staging liver biopsy specimens among chronic hepatitis C patients. (HEPATOLOGY 2011)
An event-triggered robust model predictive control (MPC) design is proposed for unknown systems using initially measured input-output data. A terminal inequality constraint is developed for the MPC ...optimization problem without any prior identification, resulting in a larger feasible region and a lower bound for the prediction horizon when compared with a terminal equality constraint. An event-triggered scheme associated with a local controller is designed to trigger the solution of the data-driven MPC optimization problem when necessary, leading to the reduction of resource consumption. Under mild conditions, recursive feasibility and input-to-state stability are guaranteed theoretically. Simulation results are provided to show the effectiveness of the proposed approach.
This work deals with the distributed Byzantine-resilient observer (DBRO) design problem for continuous-time high-order integrator multiagent systems on directed graphs, which intends to estimate the ...leader states accurately in a finite-time interval. A new kind of edge-based DBRO is first formulated for the followers to estimate each order of the nonautonomous leader's state, which is implemented in a cascading manner. Then, the finite-time zero-error estimation performance of the above DBRO is guaranteed for both time-invariant and time-varying strongly <inline-formula><tex-math notation="LaTeX">(2f+1)</tex-math></inline-formula>-robust directed topologies, based on strictly nonsmooth analysis and mathematical induction method. Finally, the practicability and validity of this new DBRO are illustrated via a numerical simulation example.
This article is concerned with event-triggered robust model predictive control for linear discrete-time systems with bounded disturbances. A two-step scheme involving a tentative verification of a ...triggering condition and a delayed triggering with a waiting horizon is proposed to reduce the average triggering rate and fully utilize the nominal optimal control sequence minimizing a quadratic cost function. The triggering condition and the waiting horizon are synthesized based on a prediction model of the plant and a robust positively invariant set associated with it. Under mild conditions, recursive feasibility and closed-loop robust stability are guaranteed. Two examples are used to show the effectiveness and merits of the proposed approach.
With machine learning techniques widely used to automate Android malware detection, it is important to investigate the robustness of these methods against evasion attacks. A recent work has proposed ...a novel problem-space attack on Android malware classifiers, where adversarial examples are generated by transforming Android malware samples while satisfying practical constraints. Aimed to address its limitations, we propose a new attack called EAGLE ( E vasion A ttacks G uided by L ocal E xplanations), whose key idea is to leverage local explanations to guide the search for adversarial examples. We present a generic algorithmic framework for EAGLE attacks, which can be customized with specific feature increase and decrease operations to evade Android malware classifiers trained on different types of count features. We overcome practical challenges in implementing these operations for four different types of Android malware classifiers. Using two Android malware datasets, our results show that EAGLE attacks can be highly effective at finding functionable adversarial examples. We study the attack transferrability of malware variants created by EAGLE attacks across classifiers built with different classification models or trained on different types of count features. Our research further demonstrates that ensemble classifiers trained from multiple types of count features are not immune to EAGLE attacks. We also discuss possible defense mechanisms against EAGLE attacks.
Novel antimicrobial nanocomposite incorporating halloysite nanotubes (HNTs) and silver (Ag) into zinc oxide (ZnO) nanoparticles is prepared by integrating HNTs and decorating Ag nanoparticles. ZnO ...nanoparticles (ZnO NPs) and Ag nanoparticles (Ag NPs) with a size of about 100 and 8 nm, respectively, are dispersively anchored onto HNTs. The synergistic effects of ZnO NPs, Ag NPs, and HNTs led to the superior antibacterial activity of the Ag-ZnO/HNTs antibacterial nanocomposites. HNTs facilitated the dispersion and stability of ZnO NPs and brought them in close contact with bacteria, while Ag NPs could promote the separation of photogenerated electron-hole pairs and enhanced the antibacterial activity of ZnO NPs. The close contact with cell membrane enabled the nanoparticles to produce the increased concentration of reactive oxygen species and the metal ions to permeate into the cytoplasm, thus induced quick death of bacteria, indicating that Ag-ZnO/HNTs antibacterial nanocomposite is a promising candidate in the antibacterial fields.
Currently, there is no “timber moment frame structural system,” as the basic glulam beam‐to‐column connections (usually represented by the bolted connections with slotted‐in steel plates) offer ...limited rotational stiffness such that they are usually treated as pin connections. This paper proposes an innovative type of moment‐resisting glulam beam‐to‐column connection reinforced by long steel rods with screwheads (LSRSs) and long self‐tapping screws (STSs). The motivation is to provide a stiff yet resilient beam‐to‐column connection that could possibly be used for the mid‐rise timber moment frame structural system without the need of shear walls or braces. Six specimens with different diameters of LSRSs were designed and experimentally tested to explore their rotational stiffness, moment‐resisting capacities, hysteretic moment‐rotation responses, and the associated failure modes. Results indicated that the proposed connection could provide not only a satisfying moment resistance, but also the energy dissipation and fast repairability that is related with structural seismic resilience. The design procedures and recommendations for the proposed connection were also provided based on the tested results. The presented experimental study serves as a handy reference for future designs and applications of the proposed connection in practical engineering projects.
In this paper, the problem of ℓ1-induced controller design for discrete-time positive systems is investigated with the use of linear Lyapunov function. An analytical method to compute the exact value ...of ℓ1-induced norm is first presented. Then, a novel characterization for stability and ℓ1-induced performance is proposed. Based on the characterization, a necessary and sufficient condition for the existence of desired controllers is derived, and an iterative convex optimization approach is developed to solve the condition. In addition, the synthesis of the state-feedback controller for single-input multiple-output (SIMO) positive systems is investigated. For this special case, an analytic solution is established to show how the optimal ℓ1-induced controller can be designed, and some links to the spectral radius of the closed-loop systems are provided. Finally, the theoretical results are illustrated through a numerical example.
PDF
