Industrial Anomaly Detection with Domain Shift: A Real-world Dataset and Masked Multi-scale Reconstruction

Industrial anomaly detection (IAD) is crucial for automating industrial quality inspection. The diversity of the datasets is the foundation for developing comprehensive IAD algorithms. Existing IAD datasets focus on the diversity of data categories, overlooking the diversity of domains within the same data category. In this paper, to bridge this gap, we propose the Aero-engine Blade Anomaly Detection (AeBAD) dataset, consisting of two sub-datasets: the single-blade dataset and the video anomaly detection dataset of blades. Compared to existing datasets, AeBAD has the following two characteristics: 1.) The target samples are not aligned and at different scales. 2.) There is a domain shift between the distribution of normal samples in the test set and the training set, where the domain shifts are mainly caused by the changes in illumination and view. Based on this dataset, we observe that current state-of-the-art (SOTA) IAD methods exhibit limitations when the domain of normal samples in the test set undergoes a shift. To address this issue, we propose a novel method called masked multi-scale reconstruction (MMR), which enhances the model's capacity to deduce causality among patches in normal samples by a masked reconstruction task. MMR achieves superior performance compared to SOTA methods on the AeBAD dataset. Furthermore, MMR achieves competitive performance with SOTA methods to detect the anomalies of different types on the MVTec AD dataset. Code and dataset are available at https://github.com/zhangzilongc/MMR.Comment: submit to Computers in Industr

Does Faith Has Impact on Investment Return: Evidence From REITs

This paper investigates whether faith has impact on investment returns. Specifically, we choose the Shariah compliance and REITs investment for the purpose of investigation. Synthetic Shariah compliant portfolios are constructed with various interpretation of compliance. We compare the performance of Shariah compliant portfolios with US Equity REIT portfolio during 1993-2017 by examining the abnormal returns using CAPM and Carhart four-factor model. We find no evidence of underperformance or outperformance of the Shariah compliant investments. This is also true during the financial crisis periods which is confirmed by the sub-sample analysis. Our findings suggest that Shariah compliant REIT investor faces no cost or gain in his investments as a result of his faith

Can rainmakers justify their pay? The role of investment banks in REIT M&As

This study explicitly rejects the prima facie proposition that the top-tier investment banks are capable of delivering supernormal value creation to the shareholders of a REIT acquirer in a corporate acquisition. Using the event study method, we find that REIT acquirers advised by market-leading investment banks suffer an average cumulative abnormal return of −4.41% following the M&A announcement, whereas REIT acquirers advised by non-top-tier investment banks only suffer an average cumulative abnormal return of −1.49%. The evidence shows that the contemporary practice of employing investment banks based on the prestige of the advisory firms could potentially result in value-destroying M&As for the REIT acquirers

Ameliorative effect of protein and calcium on fluoride-induced hepatotoxicity in rabbits

To investigate whether protein (Pr) or calcium (Ca) supplementation could ameliorate hepatic damage induced by excessive fluoride (F); thirty-two 30-day-old healthy New Zealand rabbits were randomly divided into four groups (female: male = 1:1). The four groups were maintained on distilled water and fed the following diets for 120 days: (1) a malnutrition control (MC) diet (8.58% Pr, 0.49% Ca); (2) the MC diet plus HiF (high fluoride in their diet, 200 mg F ion/kg from NaF); (3) a Ca deficient MC diet plus HiPr+HiF (0.46% Ca, 18.41% Pr, plus HiF); and (4) a Pr deficient MC diet plus HiCa+HiF (2.23% Ca, 8.35% Pr, plus HiF). Results show that in HiF group, the serum total Pr (TPr) and albumin (ALB) content significantly decreased, whereas both Pr and Ca rich diets significantly enhanced their levels. In liver, low superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities, high malondialdehyde (MDA) content, and evident mitochondria lesions in HiF group indicated a significant oxidative stress, while Pr or Ca supplementation brought an ultrastructural repair and a recovery antioxidant defense in liver. The findings in the present work implied the ameliorative effects of Pr or Ca supplementation on F-induced hepatotoxicity in rabbits.Keywords: Fluoride, hepatotoxicity, malnutrition, calcium supplementation, protein supplementatio

Role of Glycine max in improving drought tolerance in Zanthoxylum bungeanum

Intercropping may improve community stability and yield under climate change. Here, we set up a field experiment to evaluate the advantages of cultivating Z anthoxylum bungeanum with Capsicum annum, and Z. bungeanum with Glycine max as intercrops, compared with cultivating Z. bungeanum in monoculture. Effects of extreme drought stress conditions on morphological, physiological, and biochemical traits of the three crop species cultivated in the three contrasting planting systems were compared. Results showed that extreme drought conditions induced negative impacts on Z. bungeanum grown in monoculture, due to reduced growth and metabolic impairment. However, limited stomatal conductance, reduced transpiration rate (Tr), and increased water use efficiency, carotenoid content, catalase activity, and accumulation of soluble sugars in Z. bungeanum indicated its adaptive strategies for tolerance of extreme drought stress conditions. Compared with cultivation in monoculture, intercropping with C. annum had positive effects on Z. bungeanum under extreme drought stress conditions, as a result of improved crown diameter, leaf relative water content (LRWC), net photosynthetic rate, and proline content, while intercropping with G. max under extreme drought stress conditions increased net CO2 assimilation rates, LRWC, Tr , and superoxide dismutase (SOD) activity. In conclusion, Z. bungeanum has an effective defense mechanism for extreme drought stress tolerance. Intercropping with G. max enhanced this tolerance potential primarily through its physio-biochemical adjustments, rather than as a result of nitrogen fixation by G. max.Fil: Li, Zilong. Chinese Academy of Sciences; República de China. Guizhou University of Traditional Chinese Medicine; ChinaFil: Tariq, Akash. Chinese Academy of Sciences; República de China. Cele National Station of Observation and Research for Desert-Grassland Ecosystems; ChinaFil: Pan, Kaiwen. Chinese Academy of Sciences; República de ChinaFil: Graciano, Corina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Fisiología Vegetal. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Instituto de Fisiología Vegetal; ArgentinaFil: Sun, Feng. Chinese Academy of Sciences; República de ChinaFil: Song, Dagang. Biogas Institute of Ministry of Agriculture and Rural Affairs; ChinaFil: Olatunji, Olusanya Abiodun. Fujian Normal University; Chin

MGDoc: Pre-training with Multi-granular Hierarchy for Document Image Understanding

Document images are a ubiquitous source of data where the text is organized in a complex hierarchical structure ranging from fine granularity (e.g., words), medium granularity (e.g., regions such as paragraphs or figures), to coarse granularity (e.g., the whole page). The spatial hierarchical relationships between content at different levels of granularity are crucial for document image understanding tasks. Existing methods learn features from either word-level or region-level but fail to consider both simultaneously. Word-level models are restricted by the fact that they originate from pure-text language models, which only encode the word-level context. In contrast, region-level models attempt to encode regions corresponding to paragraphs or text blocks into a single embedding, but they perform worse with additional word-level features. To deal with these issues, we propose MGDoc, a new multi-modal multi-granular pre-training framework that encodes page-level, region-level, and word-level information at the same time. MGDoc uses a unified text-visual encoder to obtain multi-modal features across different granularities, which makes it possible to project the multi-granular features into the same hyperspace. To model the region-word correlation, we design a cross-granular attention mechanism and specific pre-training tasks for our model to reinforce the model of learning the hierarchy between regions and words. Experiments demonstrate that our proposed model can learn better features that perform well across granularities and lead to improvements in downstream tasks.Comment: EMNLP 202