Fault Tolerance and the Five-Second Rule

We propose a new approach to fault tolerance that we call bounded-time recovery (BTR). BTR is intended for systems that need strong timeliness guarantees during normal operation but can tolerate short outages in an emergency, e.g., when they are under attack. We argue that BTR could be a good fit for many cyber-physical systems. We also sketch a technical approach to providing BTR, and we discuss some challenges that still remain

Detecting Covert Timing Channels with Time-Deterministic Replay

This paper presents a mechanism called timedeterministic replay (TDR) that can reproduce the execution of a program, including its precise timing. Without TDR, reproducing the timing of an execution is difficult because there are many sources of timing variability – such as preemptions, hardware interrupts, cache effects, scheduling decisions, etc. TDR uses a combination of techniques to either mitigate or eliminate most of these sources of variability. Using a prototype implementation of TDR in a Java Virtual Machine, we show that it is possible to reproduce the timing to within 1.85% of the original execution, even on commodity hardware. The paper discusses several potential applications of TDR, and studies one of them in detail: the detection of a covert timing channel. Timing channels can be used to exfiltrate information from a compromised machine; they work by subtly varying the timing of the machine’s outputs, and it is this variation that can be detected with TDR. Unlike prior solutions, which generally look for a specific type of timing channel, our approach can detect a wide variety of channels with high accuracy

Unified and Dynamic Graph for Temporal Character Grouping in Long Videos

Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervised clustering to graph-based supervised clustering. However, graph methods are built upon the premise of fixed affinity graphs, bringing many inexact connections. Besides, they extract multi-modal features with kinds of models, which are unfriendly to deployment. In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping. This is accomplished firstly by a unified representation network that learns representations of multiple modalities within the same space and still preserves the modality's uniqueness simultaneously. Secondly, we present a dynamic graph clustering where the neighbors of different quantities are dynamically constructed for each node via a cyclic matching strategy, leading to a more reliable affinity graph. Thirdly, a progressive association method is introduced to exploit spatial and temporal contexts among different modalities, allowing multi-modal clustering results to be well fused. As current datasets only provide pre-extracted features, we evaluate our UniDG method on a collected dataset named MTCG, which contains each character's appearing clips of face and body and speaking voice tracks. We also evaluate our key components on existing clustering and retrieval datasets to verify the generalization ability. Experimental results manifest that our method can achieve promising results and outperform several state-of-the-art approaches

Production of high‐purity hydrogen and layered doubled hydroxide by the hydrolysis of Mg‐Al alloys

Hydrogen is becoming an important clean energy and layered doubled hydroxide (LDH) is of great interest for many applications, including water treatment, environmental remediation, and chemical catalysis. The production of high‐purity hydrogen and LDH by the hydrolysis of Mg‐Al alloys is reported. The effects of initial pH, reaction temperature, reaction time, and alloy's Mg/Al mass ratio on the rate of hydrogen generation and the purity of LDH are evaluated and the solid hydrolysis products are characterized by different techniques. The initial rate of hydrogen generation increases with decreasing initial pH and increasing reaction temperature and Mg/Al ratio while the purity of LDH increases with Mg/Al ratio, reaction temperature and time. This study may provide a new, green, and sustainable approach for storage of hydrogen and material for water treatment

A Novel Thin-Film Nanocomposite Nanofiltration Membrane by Incorporating 3D Hyperbranched Polymer Functionalized 2D Graphene Oxide

In order to develop a high-performance thin-film nanocomposite (TFN) nanofiltration (NF) membrane, the functionalized graphene-based nanomaterial (GO-HBE-COOH) was synthesized by combining two-dimensional graphene oxide (GO) with a three-dimensional hyperbranched polymer, which was used as the novel nanofiller and successfully embedded into the polypiperazine-amide (PPA) active layers on polysulfone (PSU) substrates via interfacial polymerization (IP) process. The resultant NF membranes were characterized using ATR-FTIR, SEM, and AFM, while their performance was evaluated in terms of water flux, salt rejection, antifouling ability, and chlorine resistance. The influence of GO-HBE-COOH concentration on the morphologies, properties, and performance of TFN NF membranes was investigated. With the addition of 60 ppm GO-HBE-COOH, the TFN-GHC-60 NF membrane exhibited the optimal water flux without a sacrifice of the salt rejection. It was found that the introduction of GO-HBE-COOH nanosheets favored the formation of a thinner and smoother nanocomposite active layer with an enhanced hydrophilicity and negative charge. As a result, TFN NF membranes demonstrated a superior permeaselectivity, antifouling ability, and chlorine resistance over the conventional PPA thin-film composite (TFC) membranes

Removal of Fluoride from Phosphogypsum Leaching Solution with Phosphate Tailing Based Layered Double Hydroxides: Kinetics and Equilibrium Isotherms

In this work, ternary and quaternary layered double oxides (PTB-LDO3 and PTB-LDO4) based on phosphate tailings were synthesized by the coprecipitation method. The as-prepared samples were characterized and applied to remove fluorine ions from a phosphogypsum leaching solution. The results indicated that both the precursor of PTB-LDO3 and PTB-LDO4 showed a layered structure with characteristic diffraction peaks of hydrotalcite. Compared with PTB-LDO4, PTB-LDO3 exhibited better adsorption performance at pH 5–6 and a dosage of 0.04 mg L−1. The adsorption kinetics results revealed that the adsorption of fluorine by PTB-LDO3 and PTB-LDO4 reached the adsorption equilibrium in about 3 h, and followed the pseudo-second-order model. The adsorption data could be fitted better with the Langmuir isotherm with the maximum adsorption amounts of 26.03 mg g−1 and 15.66 mg g−1 for PTB-LDO3 and PTB-LDO4, respectively. The adsorption of fluorine by PTB-LDO3 and PTB-LDO4 were both spontaneous and exothermic, and exhibited excellent reusability and stability. This study provides a possibility for the combined treatment of phosphorus chemical solid waste (phosphorus tailings) and phosphorus chemical wastewater (phosphogypsum leaching liquid)

Groundwater remediation using Magnesium–Aluminum alloys and in situ layered doubled hydroxides

In situ remediation of groundwater by zerovalent iron (ZVI)-based technology faces the problems of rapid passivation, fast agglomeration, limited range of pollutants and secondary contamination. Here a new concept of Magnesium–Aluminum (Mg–Al) alloys and in situ layered double hydroxides on is proposed for the degradation and removal of a wide variety of inorganic and organic pollutants from groundwater. The Mg–Al alloy provides the electrons for the chemical reduction and/or the degradation of pollutants while released Mg2+, Al3+ and OH- ions react to generate in situ LDH precipitates, incorporating other divalent and trivalent metals and oxyanions pollutants and further adsorbing the micropollutants. The Mg–Al alloy outperforms ZVI for treating acidic, synthetic groundwater samples contaminated by complex chemical mixtures of heavy metals (Cd2+, Cr6+, Cu2+, Ni2+ and Zn2+), nitrate, AsO33-, methyl blue, trichloroacetic acid and glyphosate. Specifically, the Mg–Al alloy achieves removal efficiency ≥99.7% for these multiple pollutants at concentrations ranging between 10 and 50 mg L−1 without producing any secondary contaminants. In contrast, ZVI removal efficiency did not exceed 90% and secondary contamination up to 220 mg L−1 Fe was observed. Overall, this study provides a new alternative approach to develop efficient, cost-effective and green remediation for water and groundwater

Data_Sheet_1_Comparative efficacy of transcranial magnetic stimulation on different targets in Parkinson’s disease: A Bayesian network meta-analysis.docx

Background/ObjectiveThe efficacy of transcranial magnetic stimulation (TMS) on Parkinson’s disease (PD) varies across the stimulation targets. This study aims to estimate the effect of different TMS targets on motor symptoms in PD.MethodsA Bayesian hierarchical model was built to assess the effects across different TMS targets, and the rank probabilities and the surface under the cumulative ranking curve (SUCRA) values were calculated to determine the ranks of each target. The primary outcome was the Unified Parkinson’s Disease Rating Scale part-III. Inconsistency between direct and indirect comparisons was assessed using the node-splitting method.ResultsThirty-six trials with 1,122 subjects were included for analysis. The pair-wise meta-analysis results showed that TMS could significantly improve motor symptoms in PD patients. Network meta-analysis results showed that the high-frequency stimulation over bilateral M1, bilateral DLPFC, and M1+DLPFC could significantly reduce the UPDRS-III scores compared with sham conditions. The high-frequency stimulation over both M1 and DLPFC had a more significant effect when compared with other parameters, and ranked first with the highest SCURA value. There was no significant inconsistency between direct and indirect comparisons.ConclusionConsidering all settings reported in our research, high-frequency stimulation over bilateral M1 or bilateral DLPFC has a moderate beneficial effect on the improvement of motor symptoms in PD (high confidence rating). High-frequency stimulation over M1+DLPFC has a prominent beneficial effect and appears to be the most effective TMS parameter setting for ameliorating motor symptoms of PD patients (high confidence rating).</p