Search

In industrial cyber-physical control systems (ICPSs), different types of variables are typically sampled at diverse intervals, ranging from subseconds to minutes or even longer, resulting in multirate sampling data. The variation in sampling rates can lead to data gaps, which impede the performance of traditional anomaly detection techniques. To address this challenge, a new anomaly detection approach is presented for ICPSs with multirate data. Employing a mechanism model (MM), it performs data super-resolution in both temporal and spatial domains, thus filling in the missing data across various sampling rates and expanding additional virtual spatial states. Moreover, the approach integrates an anomaly-forced autoencoder (AFA). The autoencoder is trained to improve anomaly detection by injecting anomalies randomly during the training phase, thereby enhancing its capacity to accurately reconstruct normal behavior under anomalous conditions. Experimental studies are conducted on a petrochemical fractionation unit simulation testbed and also a pubic benchmark dataset Battle of the Attack Detection Algorithms (BATADALs) to demonstrate the proposed approach. Experimental results from the testbed show that the proposed approach consistently maintains stable detection accuracy (ACC), ranging between 95.7% and 96.5%. On BATADAL dataset, the detection ACC varies between 87.5% and 91.5% across different multirate sampling scenarios. This performance not only outperforms state-of-the-art baseline methods but also exhibits similar superior results when applied to other datasets.

The utilization of crop straw is important for the green development of agriculture and the ecological environment. China’s agricultural planting structure is diversified and straw utilization has received increased attention. Here, in situ experiment with four types of crop straw (i.e., straw of oilseed rape, wheat, rice and corn) was conducted to analyze the effects of climate factors (i.e., accumulated temperature, AT) and straw returning methods on straw decomposition and the release of nutrients. The AT value was an important factor affecting straw decomposition and carbon, nitrogen, and phosphorus release. When straw was incorporated into the soil, the straw decomposition rate could be stimulated when the AT ≥ 600–740 °C. Under straw mulching, the decomposition rate could be further enhanced if the AT exceeded 960–1300 °C. At the end of the experiment, the decomposition and nutrient release rates increased by 39.7–148.7% and 5.8–171.5%, respectively, under straw incorporation compared to straw mulching. The differences under different returning methods in straw decomposition and nutrient release rates were higher in the summer–autumn stage (114.3–148.7% and 14.7–171.5%) than in the winter–spring stage (39.7–47.6% and 5.8–62.5%). The variance in the C/N ratio and the infrared characteristic peak of different straw types affected the decomposition rate and nutrient release characteristics. This study concludes that straw decomposition and nutrient release varied widely among different AT values, straw types, and returning methods.

Introduction: The aim of this work was to evaluate the prevalence of malignancies in a multicenter cohort of Chinese patients with immunoglobulin G4-related disease (IgG4-RD) and to identify the related risk factors of malignancy in IgG4-RD patients. Methods: We retrospectively analyzed 602 IgG4-RD patients who were recruited in five medical centers from 2009 to 2020. Standardized prevalence ratios (SPRs) against the general Chinese population were calculated along with 95% confidence intervals (CIs). We identified the risk factors of malignancy in IgG4-RD and calculated the odds ratios (ORs) of different factors. We then developed and validated a prediction model for malignancy risk of IgG4-RD based on our cohort. Results: We observed a significantly increased prevalence of total malignancies in this cohort compared to the general Chinese population (SPR 8.66 [95% CI 5.84, 12.31]). Logistic regression analysis indicated that eosinophil percentage (OR 1.096 [95% CI 1.019–1.179], P= 0.016), serum albumin-to-globulin ratio (AGR) (OR 0.185 [95% CI 0.061–0.567], P= 0.002) and autoimmune pancreatitis (OR 2.400 [95% CI 1.038–5.549], P= 0.041) were three potential risk factors of malignancy in IgG4-RD patients. Four predictors were included in our final prediction model: age at IgG4-RD diagnosis, eosinophil percentage, AGR and autoimmune pancreatitis. The nomogram performed well in the internal validation cohort, with a concordance index (C-index) of 0.738. Conclusions: A significantly increased prevalence of total malignancies was observed in our multicenter cohort. Eosinophil percentage and autoimmune pancreatitis are risk factors, whereas AGR is negatively associated with malignancy in IgG4-RD. A prediction model for malignancy risk of IgG4-RD was first developed and validated in our study.

Due to their widespread application and consequent release into aquatic environments, silver nanoparticles (AgNPs) are widely present in aquatic environments. Extracellular polymeric substances (EPS) originating from aquatic organisms are naturally biogenic polymers and may interact with nanomaterials in the environment. In this study, the impacts of EPS harvested from Chlorella vulgarison the oxidative dissolution and sulfidation of AgNPs were explored through a combination of spectral analyses and kinetic estimations. At various concentrations, algal EPS facilitated both the dissolution and sulfidation of AgNPs. The abundant aromatic groups and nitrogen containing groups were conducive to the adsorption of the algal EPS onto the surface of AgNPs. In addition, several kinds of reactive oxygen species (ROS) were generated from the EPS under light irradiation, and might actively react with AgNPs. Moreover, the abundant surface functional groups of EPS might complex with Ag+ions. These could synergistically facilitate the dissolution of AgNPs. Besides, the adsorption of EPS on AgNPs reduced the electrostatic repulsion and favored the access of sulfide to react with AgNPs, and therefore promoted the sulfidation of AgNPs to a great extent. This study provides important insights into the interaction mechanisms between EPS and AgNPs and the results are helpful to predict the fate and risk of AgNPs in complicated natural aquatic environments.

PageRank is an algorithm used by Google Search to rank web pages in their search engine results. An important step for quantum networks is to quantize the classical protocol as quantum mechanics provides computational resources that can be used to outperform classical algorithms. In this paper, we experimentally realize continuous-time quantum walks for directed graphs with non-Hermitian adjacency matrices by using linear optical circuits and single photons. We find that the node classical centrality in a directed graph is correlated with the maximum node probability resulting from a continuous-time quantum walk and then demonstrate PageRank. Our work opens up an avenue of applications of quantum information in real-life tasks.

Bulk–boundary correspondence, a guiding principle in topological matter, relates robust edge states to bulk topological invariants. Its validity, however, has so far been established only in closed systems. Recent theoretical studies indicate that this principle requires fundamental revisions for a wide range of open systems with effective non-Hermitian Hamiltonians. Therein, the intriguing localization of nominal bulk states at boundaries, known as the non-Hermitian skin effect, suggests a non-Bloch band theory in which non-Bloch topological invariants are defined in generalized Brillouin zones, leading to a general bulk–boundary correspondence beyond the conventional framework. Here, we experimentally observe this fundamental non-Hermitian bulk–boundary correspondence in discrete-time non-unitary quantum-walk dynamics of single photons. We demonstrate pronounced photon localizations near boundaries even in the absence of topological edge states, thus confirming the non-Hermitian skin effect. Facilitated by our experimental scheme of edge-state reconstruction, we directly measure topological edge states, which are in excellent agreement with the non-Bloch topological invariants. Our work unequivocally establishes the non-Hermitian bulk–boundary correspondence as a general principle underlying non-Hermitian topological systems and paves the way for a complete understanding of topological matter in open systems.

With increasing utilization of silver nanomaterials, growing concerns are raised on their deleterious effects to the environment. Once discharged in an aquatic environment, the interactions between silver nanowires (AgNWs) and proteins may significantly affect the environmental behaviors, fate, and toxicities of AgNWs. In the present study, three representative model proteins, including ovalbumin (OVA), bovine serum albumin (BSA), and lysozyme (LYZ), were applied to investigate the impacts of the interactions between proteins and AgNWs on the transformations (oxidative dissolution and sulfidation) of AgNWs in an aquatic environment. Fluorescence spectroscopy and isothermal titration calorimetry analyses indicated that there was very weak interaction between OVA or BSA and AgNWs, but there was a strong interaction between the positively charged LYZ and the negatively charged AgNWs. The presence of LYZ not only reversed the surface charge of AgNWs but also resulted in the breakup of the nanowire structure and increased the reactive surface area. The positively charged surface of AgNWs in the presence of LYZ favored the access of sulfide ions. As a consequence, the kinetics of oxidative dissolution and sulfidation of AgNWs were not affected by OVA and BSA but were significantly facilitated by LYZ. The results shed light on the important roles of electrostatic interactions between AgNWs and proteins, which may have important implications for evaluating the fate and effects of silver nanomaterials in complicated environments.

Quantitative detection of polluted gas by electronic nose can reduce the cost of detection and improve the efficiency of measurement. Through the effective pattern recognition method, the electronic nose can analyse the continuous periodic data and realise the detection of specific tasks. In this paper, the pollution gas concentration prediction method based on bidirectional long-short term memory network (Bi-LSTM) is proposed. And the effect of the Bi-LSTM model with different time steps, hidden layers and different combinations of sensor features on the performance of pollution gas prediction model is investigated. This method can extract deep features by automatically learning the gas response information of the sensor array, and its performance is better. The proposed method is verified on the air quality dataset, which proves that the proposed method has high accuracy in the quantitative detection of gas concentration based on electronic nose information.

The impacts of a model globular protein (bovine serum albumin, BSA) on aggregation kinetics of graphene oxide (GO) in aquatic environment were investigated through time-resolved dynamic light scattering at pH 5.5. Aggregation kinetics of GO without BSA as a function of electrolyte concentrations (NaCl, MgCl2, and CaCl2) followed the traditional Derjaguin–Landau–Verwey–Overbeek (DLVO) theory, and the critical coagulation concentration (CCC) was 190, 5.41, and 1.61 mM, respectively. As BSA was present, it affected the GO stability in a concentration dependent manner. At fixed electrolyte concentrations below the CCC values, for example 120 mM NaCl, the attachment efficiency of GO increased from 0.08 to 1, then decreased gradually and finally reached up to zero as BSA concentration increased from 0 to 66.5 mg C/L. The low-concentration BSA depressed GO stability mainly due to electrostatic binding between the positively charged lysine groups of BSA and negatively charged groups of GO, as well as double layer compression effect. With the increase of BSA concentration, more and more BSA molecules were adsorbed on GO, leading to strong steric repulsion which finally predominated and stabilized the GO. These results provided significant information about the concentration dependent effects of natural organic matters on GO stability under environmentally relevant conditions.

Topological edge states arise in non-Hermitian parity-time ($\mathcal {PT}$)-symmetric systems, and manifest themselves as bright or dark edge states, depending on the imaginary components of their eigenenergies. As the spatial probabilities of dark edge states are suppressed during the non-unitary dynamics, it is a challenge to observe them experimentally. Here we report the experimental detection of dark edge states in photonic quantum walks with spontaneously broken $\mathcal {PT}$symmetry, thus providing a complete description of the topological phenomena therein. We experimentally confirm that the global Berry phase in $\mathcal {PT}$-symmetric quantum-walk dynamics unambiguously defines topological invariants of the system in both the $\mathcal {PT}$-symmetry-unbroken and -broken regimes. Our results establish a unified framework for characterizing topology in $\mathcal {PT}$-symmetric quantum-walk dynamics, and provide a useful method to observe topological phenomena in $\mathcal {PT}$-symmetric non-Hermitian systems in general.Dark edge states are detected experimentally for the first time in photonic quantum walks with spontaneously broken parity-time symmetry.