Multi-scale prototype fusion network for industrial product surface anomaly detection and localization

In complex industrial application scenarios, abnormal samples are scarce. In the case of weak defect features, the high similarity of positive and negative samples further complicates detection and localization. In addition, anomalies are often subtle and unpredictable, which makes it particularly difficult to detect and localize anomalous subregions with unknown anomaly patterns. Many detection algorithms suffer from high computational complexity and huge memory consumption. To address these challenges, this paper proposes a multi-scale prototype fusion network for industrial product surface anomaly detection and localization (MPFnet). MPFnet uses multi-scale prototypes to construct representative normal patterns and incorporates a multi-scale fusion block to facilitate information exchange between different scales. This design enhances the model’s attention to characterize prototype and normal features. Feature adapter is constructed to generate fitness features, reducing domain bias. By adding noise to the adapted features, anomalous features are generated, and anomalies are detected using a simple and efficient discriminator. A large number of experiments were carried out on the challenging MVTec AD and MVTec LOCO AD datasets, demonstrating that MPFnet outperforms other state-of-the-art comparative methods, achieving good detection and localization results regardless of defect patterns

Knowledge and Determinants of Behavioral Responses to the Pandemic of COVID-19

Background: Understanding knowledge and behavioral responses to the pandemic of coronavirus disease 2019 (COVID-19) is important for appropriate public health interventions.Objectives: To assess knowledge of COVID-19 and to examine determinants associated with the adoption of preventive health behaviors among future health care providers.Methods: An anonymous online survey was sent out to pharmacy students in high and low-endemic areas of COVID-19 in China. Based on recommendations from the Chinese Center for Disease Control and Prevention, preventive health behaviors examined in this study included washing hands, wearing a face mask, and maintaining social distancing. The Health Belief Model (HBM) was used and measured by a seven-point Likert scale (one as extremely unlikely; seven as extremely likely). Multivariate linear regression models were used to examine predictors of preventive health behaviors.Results: Among 203 respondents who finished the survey, a medium level of knowledge (4.41 ± 0.95) of COVID-19 was reported. Respondents were extremely likely to wear a face mask (6.85 ± 0.60), but only moderately likely to engage in washing hands (5.95 ± 1.38) and maintaining social distancing (6.19 ± 1.60). Determinants of washing hands were cue to action, self-efficacy, knowledge, and gender; wearing a face mask were cue to action, self-efficacy, knowledge, and ethnicity; and maintaining social distancing were cue to action and self-efficacy.Conclusions: Public health interventions should consider incorporating cue to action, self-efficacy, and knowledge as factors to potentially improve the adoption of face mask-wearing, hand washing, and social distancing as appropriate individual preventive measures, especially if local and regional authorities are considering reopening schools sometime in future

Anodic Oxidation Synthesis of One-Dimensional TiO 2

One-dimensional (1D) TiO2 micro/nanostructures have received more and more attentions because of their potential applications in environmental issues. This paper reviews the most recent activities in TiO2 nanostructures with an emphasis on the authors’ own results especially on those synthesized using anodic oxidation method. The review begins with a survey of the effects of fabrication methods and the experiment conditions on the obtained TiO2 nanostructures, and then focuses on their 1D nanostructures, including the syntheses, characterizations, formation mechanisms, photocatalytic, and field emission properties. Finally, we conclude this review with the perspectives and outlooks on the future developments in this field

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5

The Supplier Selection of the Marine Rescue Equipment Based on the Analytic Hierarchy Process (AHP)-Limited Diversity Factors Method

Supplier selection is an important decision-making link in bidding activity. When overall scores of several suppliers are similar, it is hard to obtain an accurate ranking of these suppliers. Applying the Diversity Factors Method (Diversity Factors Method, DFM) may lead to over correction of weights, which would degrade the capability of indexes to reflect the importance. A Limited Diversity Factors Method (Limited Diversity Factors Method, LDFM) based on entropy is presented in this paper in order to adjust the weights, in order to relieve the over correction in DFM and to improve the capability of identification of indexes in supplier selection. An example of salvage ship bidding demonstrates the advantages of the LDFM, in which the raking of overall scores of suppliers is more accurate

Rice bran phytosterol nanoparticles: A promising approach to enhance yogurt quality and nutrition

Abstract This study aimed to improve the comprehensive utilization value of rice bran by investigating catalysts for the methyl esterification reaction of rice bran oil deodorized distillates and preparing phytosterol nanoparticles for addition to yogurt. Fe2(SO4)3 was found to be an effective catalyst, achieving a methyl esterification rate of 98.07 ± 0.23% under optimal conditions. Then, phytosterol nanoparticles were prepared and added to yogurt, resulting in stable addition with the pH decreased from 4.23 ± 0.01 to 4.02 ± 0.01 and the titratable acidity increased from 106.48 ± 0.85 °T to 117.07 ± 0.82 °T during storage. The addition of phytosterol nanoparticles increased the apparent viscosity from 0.68 ± 0.01 Pa s to 0.72 ± 0.02 Pa s and the G* from 80.01 ± 5.50 Pa to 91.80 ± 1.99 Pa, resulting in thicker and more elastic texture. Phytosterol nanoparticle improves the dispersion and stability of phytosterols in yogurt, thus making it stable to be added to yogurt. Fe2(SO4)3 is a suitable catalyst for the methyl esterification reaction of rice bran oil deodorized distillates, and the addition of rice bran phytosterol nanoparticles to yogurt can enhance its texture and nutritional value, offering a promising strategy for producing high value‐added products from rice bran

Active Intra-Abdominal Drainage Following Abdominal Digestive System Surgery: A Meta-Analysis and Systematic Review

Background Our objective is to compare the early outcomes associated with passive (gravity) drainage (PG) and active drainage (AD) after surgery. Methods Studies published until April 28, 2022 were retrieved from the PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, Web of Science databases. Results Nine studies with 14,169 patients were identified. Two groups had the same intra-abdominal infection rate (RR: 0.55; P = 0.13); In subgroup analysis of pancreaticoduodenectomy, active drainage had no significant effect on postoperative pancreatic fistula (POPF) rate (RR: 1.21; P = 0.26) and clinically relevant POPF (CR-POPF) (RR: 1.05; P = 0.72); Active drainage was not associated with lower percutaneous drainage rate (RR: 1.00; P = 0.96), incidence of sepsis (RR: 1.00; P = 0.99) and overall morbidity (RR: 1.02; P = 0.73). Both groups had the same POPF rate (RR: 1.20; P = 0.18) and CR-POPF rate (RR: 1.20; P = 0.18) after distal pancreatectomy. There was no difference between two groups on the day of drain removal after pancreaticoduodenectomy (Mean difference: −0.16; P = 0.81) and liver surgery (Mean difference: 0.03; P = 0.99). Conclusions Active drainage is not superior to passive drainage and both drainage methods can be considered