Title: Utilizing peracetic acid as an eco-friendly bleaching agent: investigating whiteness levels of cellulose microfibers from corn husk waste

Authors: Mayta, Sergio; Huamani Palomino, Ronny G.; Córdova, Bryan M.; Rivera, Ernesto; Quintana, María

Abstract: Currently, the disposal of agro-industrial waste has generated an urgent need to find eco-friendly methods to convert these wastes into value-added products like cellulose, without the use of chlorine for bleaching purposes. Based on this assumption, a comparative study was co...

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Title: Textiles Functionalized with Copper Oxides: A Sustainable Option for Prevention of COVID-19

Authors: Román, Luz Esmeralda; Villalva, Cleny; Uribe, Carmen; Paraguay Delgado, Francisco; Sousa, José; Vigo, Johnny; Mercedes Vera, Concepción; Marcela Gómez, Mónica; Solís, José&...

Abstract: COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and healthcare-associated infections (HAIs) represent severe problems in health centers and public areas. Polyester/cotton (PES/CO) blend fabrics have been functionalized with copper oxides on an industr...

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Title: Polyhydroxy Fullerenes Enhance Antibacterial and Electrocatalytic Activity of Silver Nanoparticles

Authors: Palomino, Luis; Chipoco Haro, Danae A.; Gakiya Teruya, Miguel; Zhou, Feng; La Rosa Toro, Adolfo; Krishna, Vijay; Rodriguez Reyes, Juan Carlos F.

Abstract: Silver nanoparticles (AgNPs) are known and widely used for their antibacterial properties. However, the ever-increasing resistance of microorganisms compels the design of novel nanomaterials which are able to surpass their capabilities. Herein, we synthesized silver nanoparticles using, for&...

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Title: The Potential Role of News Media to Construct a Machine Learning Based Damage Mapping Framework

Authors: Okada, Genki; Moya, Luis; Mas, Erick; Koshimura, Shunichi

Abstract: When flooding occurs, Synthetic Aperture Radar (SAR) imagery is often used to identify flood extent and the affected buildings for two reasons: (i) for early disaster response, such as rescue operations, and (ii) for flood risk analysis. Furthermore, the application of ma...

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Title: Model-based analysis of multi-UAV path planning for surveying postdisaster building damage

Authors: Nagasawa, Ryosuke; Mas, Erick; Moya, Luis; Koshimura, Shunichi

Abstract: Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In partic...

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Title: Brief communication: Radar images for monitoring informal urban settlements in vulnerable zones in Lima, Peru

Authors: Moya, Luis; Garcia, Fernando; Gonzales, Carlos; Diaz, Miguel; Zavala, Carlos; Estrada, Miguel; Yamazaki, Fumio; Koshimura, Shunichi; Mas, Erick; Adriano, Bruno

Abstract: Lima, Peru's capital, has about 9.6 million inhabitants and keeps attracting more residents searching for a better life. Many citizens, without access to housing subsidies, live in informal housing and shack settlements. A typical social phenomenon in Lima is the sudden&#x...

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Title: Disaster Intensity-Based Selection of Training Samples for Remote Sensing Building Damage Classification

Authors: Moya, Luis; GeiB, Christian; Member; IEEE; Hashimoto, Masakazu; Mas, Erick; Koshimura, Shunichi; Strunz, Günter

Abstract: Previous applications of machine learning in remote sensing for the identification of damaged buildings in the aftermath of a large-scale disaster have been successful. However, standard methods do not consider the complexity and costs of compiling a training data set after&#x...

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Title: Learning from the 2018 Western Japan Heavy Rains to Detect Floods during the 2019 Hagibis Typhoon

Authors: Moya, Luis; Mas, Erick; Koshimura, Shunichi

Abstract: Applications of machine learning on remote sensing data appear to be endless. Its use in damage identification for early response in the aftermath of a large-scale disaster has a specific issue. The collection of training data right after a disaster is costly, time-c...

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Title: Detecting urban changes using phase correlation and ℓ1-based sparse model for early disaster response: A case study of the 2018 Sulawesi&...

Authors: Moya, Luis; Muhari, Abdul; Adriano, Bruno; Koshimura, Shunichi; Mas, Erick; Marval Perez, Luis R.; Yokoya, Naoto

Abstract: Change detection between images is a procedure used in many applications of remote sensing data. Among these applications, the identification of damaged infrastructures in urban areas due to a large-scale disaster is a task that is crucial for distributing relief, quantifying&...

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