Assessment of the damage impact to particular water structures on their performance

This article aims to implement a prototype screening system to identify flooding-related photos from social media. These photos, associated with their geographic locations, can provide free, timely, and reliable visual information about flood events to the decision-makers. This screening system, designed for application to social media images, includes several key modules: tweet/image downloading, flooding photo detection, and a WebGIS application for human verification. In this study, a training dataset of 4800 flooding photos was built based on an iterative method using a convolutional neural network (CNN) developed and trained to detect flooding photos. The system was designed in a way that the CNN can be re-trained by a larger training dataset when more analyst-verified flooding photos are being added to the training set in an iterative manner. The total accuracy of flooding photo detection was 93% in a balanced test set, and the precision ranges from 46–63% in the highly imbalanced real-time tweets. The system is plug-in enabled, permitting flexible changes to the classification module. Therefore, the system architecture and key components may be utilized in other types of disaster events, such as wildfires, earthquakes for the damage/impact assessment.

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Protective Role of Epigallocatechin Gallate in a Rat Model of Cisplatin-Induced Cerebral Inflammation and Oxidative Damage: Impact of Modulating NF-κB and Nrf2

Neurotoxicity Research ◽

10.1007/s12640-019-00095-x ◽

2019 ◽

Vol 37 (2) ◽

pp. 380-396 ◽

Cited By ~ 3

Author(s):

Manar Hamed Arafa ◽

Hebatallah Husseini Atteia

Keyword(s):

Oxidative Damage ◽

Rat Model ◽

Epigallocatechin Gallate ◽

Protective Role ◽

Cerebral Inflammation ◽

Damage Impact

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Study on the drop impact characteristics and impact damage mechanism of sweet potato tubers during harvest

PLoS ONE ◽

10.1371/journal.pone.0255856 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255856

Author(s):

Guocheng Bao ◽

Gongpu Wang ◽

Bing Wang ◽

Lianglong Hu ◽

Xiaowei Xu ◽

...

Keyword(s):

Mathematical Model ◽

Sweet Potato ◽

Damage Mechanism ◽

Drop Height ◽

Potato Tubers ◽

Impact Stress ◽

Chunk Size ◽

The Impact ◽

Damage Impact ◽

Critical Damage

Collision of falling in the mechanical harvesting process of sweet potato is one of the main causes of epidermal destruction and damage to sweet potato tubers. Therefore, a sweet potato mechanical characteristic test and a full-factor sweet potato drop test were designed. Based on the analysis of the fitting mathematical model, the impact of the drop height, collision material and sweet potato chunk size on the damage of the sweet potato were studied. The mathematical models were established by fitting analysis of the IBM SPSS Statistics 22 software between the drop height and the sweet potato chunk size with each test index (impact force, impact stress, broken skin area and damaged area). The critical epidermal destruction height and the critical damage height of a certain size of sweet potato when it collides with a collision material can be calculated by the mathematical model, and the critical epidermal destruction mass and critical damage mass of sweet potato when it falls from a certain height and collides with a collision material can also be calculated. Then a series of critical values (including critical epidermal destruction force value, critical epidermal destruction impact stress, critical damage force value, critical damage impact stress) of mechanical properties of sweet potato were obtained. The results show that the impact deformation of sweet potato includes both elastic and plastic ones, and has similar stress relaxation characteristics. The critical damage impact stress of sweet potato is that the average value of the impact stress on the contact surface is less than it’s Firmness. The results provided a theoretical basis for understanding the collision damage mechanism of sweet potato and how to reduce the damage during harvest.

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