Deep Industrial Image Anomaly Detection: A Survey

The recent rapid development of deep learning has laid a milestone in industrial Image Anomaly Detection (IAD). In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural network architectures, levels of supervision, loss functions, metrics and datasets. In addition, we extract the new setting from industrial manufacturing and review the current IAD approaches under our proposed our new setting. Moreover, we highlight several opening challenges for image anomaly detection. The merits and downsides of representative network architectures under varying supervision are discussed. Finally, we summarize the research findings and point out future research directions. More resources are available at https://github.com/M-3LAB/awesome-industrial-anomaly-detection

Scalable synthesis of multicomponent multifunctional inorganic core@mesoporous silica shell nanocomposites

Integrating multiple materials with different functionalities in a single nanostructure enables advances in many scientific and technological applications. However, such highly sophisticated nanomaterials usually require complex synthesis processes that complicate their preparation in a sustainable and industrially feasible manner. Herein, we designed a simple general method to grow a mesoporous silica shell onto any combination of hydrophilic nanoparticle cores. The synthetic strategy, based on the adjustment of the key parameters of the sol-gel process for the silica shell formation, allows for the embedment of single, double, and triple inorganic nanoparticles within the same shell, as well as the size-control of the obtained nanocomposites. No additional interfacial adhesive layer is required on the nanoparticle surfaces for the embedding process. Adopting this approach, electrostatically stabilized, small-sized (from 4 to 15 nm) CeO2, Fe3O4, Gd2O3, NaYF4, Au, and Ag cores were used to test the methodology. The mean diameter of the resulting nanocomposites could be as low as 55 nm, with high monodispersity. These are very feasible sizes for biological intervention, and we further observed increased nanoparticle stability in physiological environments. As a demonstration of their increased activity as a result of this, the antioxidant activity of CeO2 cores was enhanced when in core-shell form. Remarkably, the method is conducted entirely at room temperature, atmospheric conditions, and in aqueous solvent with the use of ethanol as co-solvent. These facile and even "green" synthesis conditions favor scalability and easy preparation of multicomponent nanocomposite libraries with standard laboratory glassware and simple benchtop chemistry, through this sustainable and cost-effective fabrication process.This work was financially supported by the National Natural Science Foundation of China (31950410536 to E.C. and 22005221 to M.Z.), the Wuyi University (2018TP010 to E.C., 2018TP011 and 2020FKZX05 to M.Z., and 2019TD02 to J.P.), Guangdong Science and Technology Department (2019A050512006 to E.C.), the Academy of Finland (309374 to J.M.R.), and the Instituto de Salud Carlos III of Spain (PI19/00774 to G.F-V and G.C.), co-financed by FEDER, European Union, “A way of making Europe”

Identification of QTLs for Arsenic Accumulation in Maize (Zea mays L.) Using a RIL Population

The Arsenic (As) concentration in different tissues of maize was analyzed using a set of RIL populations derived from an elite hybrid, Nongda108. The results showed that the trend of As concentration in the four measured tissues was leaves>stems>bracts>kernels. Eleven QTLs for As concentration were detected in the four tissues. Three QTLs for As concentration in leaves were mapped on chromosomes 1, 5, and 8, respectively. For As concentration in the bracts, two QTLs were identified, with 9.61% and 10.03% phenotypic variance. For As concentration in the stems, three QTLs were detected with 8.24%, 14.86%, and 15.23% phenotypic variance. Three QTLs were identified for kernels on chromosomes 3, 5, and 7, respectively, with 10.73%, 8.52%, and 9.10% phenotypic variance. Only one common chromosomal region between SSR marker bnlg1811 and umc1243 was detected for QTLs qLAV1 and qSAC1. The results implied that the As accumulation in different tissues in maize was controlled by different molecular mechanism. The study demonstrated that maize could be a useful plant for phytoremediation of As-contaminated paddy soil, and the QTLs will be useful for selecting inbred lines and hybrids with low As concentration in their kernels

Antibiofilm Activity of an Exopolysaccharide from Marine Bacterium Vibrio sp. QY101

Bacterial exopolysaccharides have always been suggested to play crucial roles in the bacterial initial adhesion and the development of complex architecture in the later stages of bacterial biofilm formation. However, Escherichia coli group II capsular polysaccharide was characterized to exert broad-spectrum biofilm inhibition activity. In this study, we firstly reported that a bacterial exopolysaccharide (A101) not only inhibits biofilm formation of many bacteria but also disrupts established biofilm of some strains. A101 with an average molecular weight of up to 546 KDa, was isolated and purified from the culture supernatant of the marine bacterium Vibrio sp. QY101 by ethanol precipitation, iron-exchange chromatography and gel filtration chromatography. High performance liquid chromatography traces of the hydrolyzed polysaccharides showed that A101 is primarily consisted of galacturonic acid, glucuronic acid, rhamnose and glucosamine. A101 was demonstrated to inhibit biofilm formation by a wide range of Gram-negative and Gram-positive bacteria without antibacterial activity. Furthermore, A101 displayed a significant disruption on the established biofilm produced by Pseudomonas aeruginosa, but not by Staphylococcus aureus. Importantly, A101 increased the aminoglycosides antibiotics' capability of killing P. aeruginosa biofilm. Cell primary attachment to surfaces and intercellular aggregates assays suggested that A101 inhibited cell aggregates of both P. aeruginosa and S. aureus, while the cell-surface interactions inhibition only occurred in S. aureus, and the pre-formed cell aggregates dispersion induced by A101 only occurred in P. aeruginosa. Taken together, these data identify the antibiofilm activity of A101, which may make it potential in the design of new therapeutic strategies for bacterial biofilm-associated infections and limiting biofilm formation on medical indwelling devices. The found of A101 antibiofilm activity may also promote a new recognition about the functions of bacterial exopolysaccharides

New Sequential Fractional Differential Equations with Mixed-Type Boundary Conditions

In this paper, we introduce new sequential fractional differential equations with mixed-type boundary conditions CDq+kCDq−1ut=ft,ut,CDq−1ut,t∈0,1,α1u0+β1u1+γ1Iruη=ε1,η∈0,1,α2u′0+β2u′1+γ2Iru′η=ε2, where q∈1,2 is a real number, k,r>0,αi,βi,γi,εi∈ℝ,i=1,2,CDq is the Caputo fractional derivative, and the boundary conditions include antiperiodic and Riemann-Liouville fractional integral boundary value cases. Our approach to treat the above problem is based upon standard tools of fixed point theory and some new inequalities of norm form. Some existence results are obtained and well illustrated through the aid of examples

Real-time prediction of earthquake potential damage: A case study for the January 8, 2022 MS 6.9 Menyuan earthquake in Qinghai, China

It is critical to determine whether a site has potential damage in real-time after an earthquake occurs, which is a challenge in earthquake disaster reduction. Here, we propose a real-time Earthquake Potential Damage predictor (EPDor) based on predicting peak ground velocities (PGVs) of sites. The EPDor is composed of three parts: (1) predicting the magnitude of an earthquake and PGVs of triggered stations based on the machine learning prediction models; (2) predicting the PGVs at distant sites based on the empirical ground motion prediction equation; (3) generating the PGV map through predicting the PGV of each grid point based on an interpolation process of weighted average based on the predicted values in (1) and (2). We apply the EPDor to the 2022 MS 6.9 Menyuan earthquake in Qinghai Province, China to predict its potential damage. Within the initial few seconds after the first station is triggered, the EPDor can determine directly whether there is potential damage for some sites to a certain degree. Hence, we infer that the EPDor has potential application for future earthquakes. Meanwhile, it also has potential in Chinese earthquake early warning system

Preparation, Characterization, and Evaluation of Breviscapine Nanosuspension and Its Freeze-Dried Powder

As a biopharmaceutics classification system (BCS) class IV drug, breviscapine (Bre) has low solubility in water, poor chemical stability, a short biological half-life and rapid removal from plasma. This paper prepared a Bre nanosuspension (Bre-NS) by an ultrasound-assisted anti-solvent precipitation method. Characterization of Bre-NS was studied using a Box–Behnken design concerning drug concentration in DMSO, an anti-solvent-to-solvent ratio, and sonication time. Under the optimized conditions of 170 mg/mL for the drug concentration, a 1:60 solvent-to-anti-solvent ratio, and a 9 min sonication time, the particle size of Bre-NS was 303.7 ± 7.3 nm, the polydispersity index was 0.178 ± 0.015, and the zeta potential was −31.10 ± 0.26 mV. Combined with the results from differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), and Fourier transform-infrared spectroscopy (FT-IR), the findings indicated that the crystal form and chemical structure of Bre-NS did not change during the entire process. The optimized formulation displayed good stability, increased solubility, and better in vitro release. Therefore, the results of this study can be a reference for the delivery system design of insoluble active components and effective parts in traditional Chinese medicine

Characterization and optical properties of (Gd1−x, Prx)2O2S nano-phosphors synthesized using a novel co-precipitation method

A novel co-precipitation method for synthesizing (Gd1-x, Prx)2O2S nano-phosphors was developed, using the commercially available Gd2O3, Pr6O11, H2SO4 and NaOH as the starting materials. This method has the advantage of controllable phosphor particle size and shape, simplicity in processing, low cost, and not involving toxic carbon disulfide or hydrogen sulfide. It was found that the as-synthesized precursor is mainly composed of (Gd1-x, Prx)2(OH)4SO4·nH2O. By calcining the (Gd1-x, Prx)2(OH)4SO4·nH2O precursor at a temperature higher than 700 ◦C for 1 h in flowing hydrogen, pure quasi-spherical shaped (Gd1-x,Prx)2O2S particles can be synthesized. The (Gd1-x, Prx)2O2S particles have a narrow size distribution with a mean grain size of about 20-30 nm. UV-vis spectra indicates that the absorption edge of the samples has a blue shift with increasing calcination temperature, while PL spectra of (Gd1-x, Prx )2O2S under 301nm excitation show a green emission at 511nm as the most prominent peak, which corresponds to the 3P0→3H4 transition of Pr3+ ions. The optimal x value is 0.01 for the highest luminescent emission intensity