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Waste Products

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Physicochemical characterization of an arabinoxylan-rich fraction from brewers' spent grain and its application as a release matrix for caffeine.

Food research international (Ottawa, Ont.)
The brewers' spent grain is a by-product generated during brewery process and is a potential source for arabinoxylans (AX) extraction. In the present work, the extraction and characterization of an arabinoxylan-rich fraction from brewers' spent grain...

Marine litter accumulation along the Bulgarian Black Sea coast: Categories and predominance.

Waste management (New York, N.Y.)
Quantitative assessment of marine litter (ML) along the Bulgarian Black Sea coastline was presented. ML surveys were conducted every season in a total of 8 beach monitoring sites during 2015-2016. Eight main categories of material were determined, ba...

Ultrasonic pretreatment of food waste to accelerate enzymatic hydrolysis for glucose production.

Ultrasonics sonochemistry
Recovering valuable materials from food waste by applying the concept of a bio-refinery is attracting considerable interest. To this effect, we investigated the possibility of enhancing the enzymatic hydrolysis of food waste using ultrasonic technolo...

Multilayer Hybrid Deep-Learning Method for Waste Classification and Recycling.

Computational intelligence and neuroscience
This study proposes a multilayer hybrid deep-learning system (MHS) to automatically sort waste disposed of by individuals in the urban public area. This system deploys a high-resolution camera to capture waste image and sensors to detect other useful...

Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international
Estimating the volume of macro-plastics which dot the world's oceans is one of the most pressing environmental concerns of our time. Prevailing methods for determining the amount of floating plastic debris, usually conducted manually, are time demand...

Rummaging through the bin: Modelling marine litter distribution using Artificial Neural Networks.

Marine pollution bulletin
Marine litter has significant ecological, social and economic impacts, ultimately raising welfare and conservation concerns. Assessing marine litter hotspots or inferring potential areas of accumulation are challenging topics of marine research. Neve...

An intelligent way for discerning plastics at the shorelines and the seas.

Environmental science and pollution research international
Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network...

Automatic detection of seafloor marine litter using towed camera images and deep learning.

Marine pollution bulletin
Aerial and underwater imaging is being widely used for monitoring litter objects found at the sea surface, beaches and seafloor. However, litter monitoring requires a considerable amount of human effort, indicating the need for automatic and cost-eff...

A comparative study of deep learning-based network model and conventional method to assess beach debris standing-stock.

Marine pollution bulletin
The conventional survey of marine debris standing-stock has various drawbacks such as high cost and inaccuracy because the total amount of debris in the whole beach is inferred using the results of the manual investigation in selected narrow areas. T...

MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data.

PloS one
Currently, a significant amount of research is focused on detecting Marine Debris and assessing its spectral behaviour via remote sensing, ultimately aiming at new operational monitoring solutions. Here, we introduce a Marine Debris Archive (MARIDA),...