FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation

Although industrial anomaly detection (AD) technology has made significant progress in recent years, generating realistic anomalies and learning priors of normal remain challenging tasks. In this study, we propose an end-to-end industrial anomaly detection method called FractalAD. Training samples are obtained by synthesizing fractal images and patches from normal samples. This fractal anomaly generation method is designed to sample the full morphology of anomalies. Moreover, we designed a backbone knowledge distillation structure to extract prior knowledge contained in normal samples. The differences between a teacher and a student model are converted into anomaly attention using a cosine similarity attention module. The proposed method enables an end-to-end semantic segmentation network to be used for anomaly detection without adding any trainable parameters to the backbone and segmentation head, and has obvious advantages over other methods in training and inference speed.. The results of ablation studies confirmed the effectiveness of fractal anomaly generation and backbone knowledge distillation. The results of performance experiments showed that FractalAD achieved competitive results on the MVTec AD dataset and MVTec 3D-AD dataset compared with other state-of-the-art anomaly detection methods.Comment: 12 pages, 5 figure

On the issue of transparency and reproducibility in nanomedicine.

Following our call to join in the discussion over the suitability of implementing a reporting checklist for bio-nano papers, the community responds

Simultaneous removal of organic micropollutants and inorganic heavy metals by nano-calcium peroxide induced Fenton-like treatment

Groundwater can be contaminated by both organic micropollutants and inorganic heavy metals and thus, it is essential to develop environmental-friendly and cost-effective technologies for the remediation of such multiple contaminants. Advanced nanomaterials, including nano-calcium peroxide (nano-CaO2), induced Fenton-like treatment has been recently developed to effectively oxidise and remediate various organic micropollutants. The Ca(OH)2 residues have the potential to further remove toxic heavy metals via precipitation, however, it has been rarely studied. To investigate the proposed feasibility and understand the mechanisms, an optimised pH-regulated chemical precipitation method was developed to synthesis the nano-CaO2 material and then catalysed by Fe(II) towards simultaneous removal of the model compounds of p-nitrophenol (PNP) and cadmium (Cd). The Electron Spin Resonance (ESR) measurements demonstrated that hydroxyl radicals (∙OH) and singlet oxygen (1O2) are two major reactive oxygen species that lead to 93 % removal of PNP under the initial concentration of 40 mg/L. Simultaneously, over 99 % of the Cd (initial concentration of 10 mg/L) was removed through the precipitation with Ca(OH)2 and/or co-precipitation with ferrite. Such best removal performances were achieved under the optimal dose ratio of nano-CaO2 and Fe(II) at 500 mg/L to 75 mg/L, respectively. The existence of sunlight illumination and competition ions, i.e. K+, Na+, Ca2+, Mg2+, SO42-, NO3–, and Cl−, showed negligible effect on the removal performance, which supported its feasibility for the treatment of both ground- and surface water. Increasing the pH to 9, the time to remove 99 % Cd would be shortened from 60 min to 30 min, however, the degradation of PNP would dramatically reduce from 93 % to 20 % with 180 min. The removal performance was not affected by a large range of anions and cations, such as Na+, K+, Ca2+, Mg2+, Fe3+, SO42−, Cl− and NO3– ions, however, the existence of HCO3– and Mn2+ should be taken into consideration during the application as they could lead to obvious impacts on the treatment. Overall, this study provided a new insight of removing organic micropollutants and inorganic heavy metals simultaneously from groundwater via mechanisms revealed ex-situ nano-remediation technique

Effects of harvest time and added molasses on nutritional content, ensiling characteristics and degradation of whole crop wheat

Objective Wheat is an alternative to corn silage for ruminant feeding in northern China. This study examined the effects of harvest time and added molasses on nutritional content, ensiling characteristics and in vitro degradation of whole crop wheat (WCW). Methods Fresh WCW at the milk-ripe stage was harvested at 0700 h (i.e., in the morning [Mo]) and 1700 h (i.e., in the afternoon [Af]), and then immediately used to prepare silage and make hay. Commercial molasses was added to Af WCW at 0%, 2%, 4%, and 6% (fresh weight) proportions. The WCW treated with molasses was mixed thoroughly prior to ensiling. Results Dry matter (DM), neutral detergent fiber, water soluble carbohydrate (WSC) content (p<0.01), accumulative gas production in 72 h (GP72h, 77.46 mL/g vs 95.15 mL/g) and dry matter disappearance in vitro (69.15% vs 76.77%) were lower (p<0.05), while crude protein (CP) content was higher for WCW silage (WCWS) compared to WCW (p<0.01). The propionic acid and butyric acid concentrations in WCWS from Mo WCW were 1.47% and 0.26%, respectively. However, the propionic and butyric acid concentrations were negligible, while the ammonia nitrogen/total nitrogen (NH3-N/TN, p<0.01) concentration was lower and the rate of gas production at 50% of the maximum (17.05 mL/h vs 13.94 mL/h, p<0.05) was higher for Af WCWS compared to Mo WCWS. The incubation fluid’s NH3-N concentration was lower in WCWS and Af WCW compared to Mo WCW (p<0.05). The CP and WSC content increased with increasing molasses levels (p<0.05). Furthermore, the pH (p<0.01) and time when gas production was 50% of the maximum (2.78 h vs 3.05 h, p<0.05) were lower in silage treated with 4% molasses than silage without molasses. Conclusion Harvesting wheat crops in the afternoon and adding molasses at 4% level to WCW optimally improved ensiling characteristics, leading to well-preserved silage

20(S)-Protopanaxadiol Phospholipid Complex: Process Optimization, Characterization, In Vitro Dissolution and Molecular Docking Studies

20(S)-Protopanaxadiol (PPD), a bioactive compound extracted from ginseng, possesses cardioprotective, neuroprotective, anti-inflammatory, antiestrogenic, anticancer and anxiolytic effects. However, the clinical application of PPD is limited by its weak aqueous solubility. In this study, we optimized an efficient method of preparing its phospholipid complex (PPD-PLC) using a central composite design and response surface analysis. The prepared PPD-PLC was characterized by differential scanning calorimetric, powder X-ray diffraction, Fourier-transformed infrared spectroscopy and nuclear magnetic resonance analyses associated with molecular docking calculation. The equilibrium solubility of PPD-PLC in water and n-octanol increased 6.53- and 1.53-times, respectively. Afterwards, using PPD-PLC as the intermediate, the PPD-PLC-loaded dry suspension (PPD-PLC-SU) was prepared with our previous method. In vitro evaluations were conducted on PPD-PLC and PPD-PLC-SU, including dissolution behaviors and stability properties under different conditions. Results of in vitro dissolution behavior revealed the improved dissolution extents and rates of PPD-PLC and PPD-PLC-SU (p &lt; 0.05). Results of the formulation stability investigation also exposed the better stability of PPD-PLC-SU compared with free PPD. Therefore, phospholipid complex technology is a useful formulation strategy for BCS II drugs, as it could effectively improve their hydrophilicity and lipophilicity

Excess Body Mass Index and Risk of Liver Cancer: A Nonlinear Dose-Response Meta-Analysis of Prospective Studies

<div><h3>Background</h3><p>Excess body weight measured as body mass index (BMI) has a positive association with risk of common cancers. However, previous meta-analyses related to BMI and liver cancer had inconsistent results. The purpose of the current study is to establish a nonlinear dose-response relationship between BMI and incidence risk of liver cancer.</p> <h3>Methods</h3><p>A systematic literature search for relevant articles published from 1966 to November 2011 was conducted in PUBMED and EMBASE digital databases. Additional articles were manually searched by using the reference lists of identified papers. Restricted cubic splines and generalized least-squares regression methods were used to model a potential curvilinear relationship and to make a dose-response meta-analysis. Stratified analysis, sensitivity analysis and assessment of bias were performed in our meta-analysis.</p> <h3>Results</h3><p>8 articles including 1,779,471 cohort individuals were brought into meta-analysis. A non-linear dose-response association between BMI and risk of liver cancer was visually significant (<em>P</em> for nonlinearity<0.001), besides, the point value of BMI also enhanced the results quantitatively, where relative risks were 1.02 (95%CI = 1.02–1.03), 1.35 (95%CI = 1.24–1.47) and 2.22-fold (95%CI = 1.74–2.83) when BMI was at the point of 25, 30 and 35 kg/m² compared with reference (the median value of the lowest category), respectively. The ethnicity of the population was found as the main source of heterogeneity. In subsequent stratified analysis, no evidence of heterogeneity was showed in Asian and White populations (<em>P</em> for heterogeneity>0.1), and all value of BMI still presented significantly increased risk of cancer.</p> <h3>Conclusions</h3><p>The findings from meta-analysis provided that excess BMI had significant increased association with risk of liver cancer, although the biological mechanisms underlying the obesity-cancer link still need to be clarified.</p> </div

The curve of body mass index and relative risk of liver cancer in White population.

<p>The curve of body mass index and relative risk of liver cancer in White population.</p

The curve of body mass index and relative risk of liver cancer in Asian population.

<p>The curve of body mass index and relative risk of liver cancer in Asian population.</p

Nonlinear dose-response analyses of body mass index and relative risk of liver cancer in meta-analysis.

<p>(<i>P</i>-heterogeneity = 0.001; <i>P</i>-non-linear<0.001).</p