Polysaccharides in Agro-Industrial Biomass Residues

The large-scale industrial use of polysaccharides to obtain energy is one of the most discussed subjects in science. However, modern concepts of biorefinery have promoted the diversification of the use of these polymers in several bioproducts incorporating concepts of sustainability and the circular economy. This work summarizes the major sources of agro-industrial residues, physico-chemical properties, and recent application trends of cellulose, chitin, hyaluronic acid, inulin, and pectin. These macromolecules were selected due to their industrial importance and valuable functional and biological applications that have aroused market interests, such as for the production of medicines, cosmetics, and sustainable packaging. Estimations of global industrial residue production based on major crop data from the United States Department of Agriculture were performed for cellulose content from maize, rice, and wheat, showing that these residues may contain up to 18%, 44%, and 35% of cellulose and 45%, 22%, and 22% of hemicellulose, respectively. The United States (~32%), China (~20%), and the European Union (~18%) are the main countries producing cellulose and hemicellulose-rich residues from maize, rice, and wheat crops, respectively. Pectin and inulin are commonly obtained from fruit (~30%) and vegetable (~28%) residues, while chitin and hyaluronic acid are primarily found in animal waste, e.g., seafood (~3%) and poultry (~4%).

Association between dietary choline and betaine intake and 10.6-year cardiovascular disease in adults

Background Several studies have assessed the association between dietary choline and betaine and cardiovascular disease (CVD), but their results are inconsistent. The present study aimed to determine the association between dietary intake of choline and betaine and the risk of CVD in the general population over a 10.6-year period of follow-up. Methods The present cohort study was conducted on participants in the third wave of the Tehran Lipid and Glucose Study (2006–2008) and was followed-up until March 2018. Dietary intake of choline and betaine was calculated using the United States Department of Agriculture (USDA) database. Patients’ medical records were used to collect data on CVD. Results In this study, 2606 subjects with no previous CVD participated and were followed-up for a median of 10.6 years. During the follow-up periods, 187 incidences of CVD were detected. Results of the Cox proportional hazards regression indicated that neither energy-adjusted total choline nor betaine was associated with the incidence of CVD. Among individual choline forms, only higher intake of free choline (FC) was associated with a lower risk of CVD (HR: 0.64, 95% CI: 0.42–0.98). There was no significant association between each 10 mg/d increase in choline and betaine content of each food category and CVD. Conclusion Our investigation indicates no association between energy-adjusted total choline and betaine and a 10.6-year risk of CVD among adults. Besides, we found no relationship between individual choline forms (except FC) and CVD. We also found energy-adjusted choline and betaine obtained from food categories were not associated with the risk of CVD.

Neural Network Based Estimation of Service Life of Different Metal Culverts in Arkansas

The Arkansas Department of Transportation (ARDOT) uses different types of metal culverts and cross-drains. Service lives of these culverts are largely influenced by the corrosion of the metals used in these culverts. Corrosion of metallic parts in any soil-water environment is governed by geochemical and electrochemical properties of the soils and waters. Many transportation agencies including ARDOT primarily focus on investigating the physical and mechanical properties of soils rather than their chemical aspects. The main objective of this study is to analyze the geotechnical and geochemical properties of soils in Arkansas to estimate the service lives of different metal pipes in different conditions. Soil resistivity values were predicted after analyzing the United States Department of Agriculture (USDA) soil survey data using neural network (NN) models. The developed NN models were trained and verified by using laboratory test results of soil samples collected from ARDOT, and survey data were obtained from the USDA. The service lives of metal culverts were then estimated based on the predicted soil properties and water quality parameters extracted from the data acquired from the Arkansas Department of Environmental Quality (ADEQ). Finally, Geographic Information System-based corrosion risk maps of three different types of metal pipes were developed based on their estimated service lives. The developed maps will help ARDOT engineers to assess the corrosion potential of the metal pipes before starting the new construction and repair projects and will allow using proper culvert materials to maximize their life spans.

COMPARATIVE ANALYSIS OF THE US IMPORTATION SEASONALITY OF WOODEN MOLDINGS MADE OUT OF BRAZILIAN AND CHILEAN CONIFERS

Conifer wood moldings are classified as high value-added wood products and are used for several purposes in civil construction. Brazil is the world’s leading exporter of this product and the United States are its main destination market. It is very important to analyze the behavior of such importations and exportations to set strategies to obtain or increase the competitive advantage and improve the commercialization of these products. The objective of this study was to analyze the US importation seasonality of conifer wood moldings from Brazil and Chile, the main competitor of the Brazilian product in the US market. To write this paper, monthly data of the quantity of US importations of Brazilian and Chilean moldings from the period of 2011 to 2017 were collected from the database of the United States Department of Agriculture/Foreign Agricultural Service. The methodology proposed by Hoffman (2006) was employed to calculate the seasonal and seasonality indexes. The results indicated that the US importation of conifer wood moldings, both from Brazil and Chile, have a seasonal behavior, with great variation of the seasonal index.

Comparative analysis of the competitiveness of Beninese and Brazilian cotton exports in international trade from 2006 to 2018

This study aims to analyze the competitiveness and orientation of Brazilian and Beninese cotton exports in international trade from 2006 to 2018. The cotton category in this article refers to “neither carded nor combed” (HS: 5201). To measure competitiveness, we chose to calculate the Revealed Comparative Advantage Index (RCAI) and Symmetric Revealed Comparative Advantage Index (SRCAI), proposed by Balassa (1965) and Laursen (1998) respectively. The Regional Orientation Index (ROI), proposed by Yeats (1997), of cotton for Asia and EU-28 is used. The data were collected from the International Trade Center (ITC) /Trade Map and the United States Department of Agriculture (USDA). The results found indicate that the Brazilian’s and Beninese’s cotton has been increasing values and above the unit showing its competitiveness in the international market. In addition, Benin was more competitive than Brazil because it has, on average, a higher SRCAI than Brazil (0.99 and 0.7 respectively). Concerning the ROI, it was found that Brazilian and Beninese cotton exports are strongly directed towards Asia, the main consumer market for Beninese and Brazilian cotton. As for the EU-28, both Benin and Brazil do not direct their cotton sales to this economic block.

Overview of Big Data and Its Visualization

Big Data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. This chapter discusses what Big Data is and its characteristics, and how this information revolution of Big Data is transforming our lives and the new technology and methodologies that have been developed to process data of these huge dimensionalities. This chapter discusses the components of the Big Data stack interface, categories of Big Data analytics software and platforms, descriptions of the top 20 Big Data analytics software. Big Data visualization techniques are discussed with real data from fatality analysis reporting system (FARS) managed by National Highway Traffic Safety Administration (NHTSA) of the United States Department of Transportation. Big Data web-based visualization software are discussed that are both JavaScript-based and user-interface-based. This chapter also discusses the challenges and opportunities of using Big Data and presents a flow diagram of the 30 chapters within this handbook.

Overidentification of English Language Learners for Special Education

Alarming statistics presented by the United States Department of Education reveal a disproportionate number of students of minority language (English language learners) qualify for special education. As far back as 2007, the DOE recognized there was a concerted effort needed to reduce racial and ethnic disproportionality in racial and ethnic identification, placement, and disciplinary actions for minority students' representation in special education. This chapter will examine and address solutions to prevent the over identification of English language learners in special education specifically in the area of identification. As a further objective, the ramifications of this over representation will be examined, and the authors hypothesize about why the over representation occurs. Confusion over the Unz Initiative (1998, Proposition 227) may have inadvertently led to the over identification. A case study, leading to case law, concludes the chapter.

Reviewer Acknowledgements for Journal of Food Research, Vol. 10 No. 6

Journal of Food Research wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated. Journal of Food Research is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please contact us for the application form at: [email protected] Reviewers for Volume 10, Number 6 Antonello Santini, University of Napoli "Federico II", Italy Corina-aurelia Zugravu, University of Medicine and Pharmacy Carol Davila, Romania Elke Rauscher-Gabernig, Austrian Agency for Health and Food Safety, Austria Elsa M Goncalves, Instituto Nacional de Investigacao Agrária (INIA), Portugal Jose Maria Zubeldia, Clinical Regulatory Consultant for the HIV & Hepatitis C initiative at Drugs for Neglected Diseases Initiative, Spain Lucas Massaro Sousa, IFP Energies Nouvelles, France Meena Somanchi, United States Department of Agriculture, United States Sefat E Khuda, Centre for Food Safety and Applied Nutrition, United States Xingjun Li, Academy of the National Food and Strategic Reserves Administration, China

Assessment of Soil Texture on Triticum aestivum Growth

Soil texture is an important environmental factor that influences the crop productivity of wheat (Triticum aestivum) because it provides all the nutrients required for growth of the plants. The soil based on nutrients is classified into four classes: silt, clay, sand, and loam. Soil based on mineral particles was classified by the United States Department of Agriculture (USDA). According to USDA, loam particles have a size between sand (2.00–1.0 mm) and silt (0.05–0.002 mm), whereas clay is less than 0.002 mm. Analysis shows that the growth rate of Triticum aestivum in each soil sample is different. The sizes of seven plants were increased in loamy soil, to 47 cm, whereas in sandy soil, plants were 25 cm long. Seven plants were grown in clay soil, and had lengths of 28 cm. Finally, five plants were grown in silt soil, and reached a size of 38 cm. After fertilizing each plant in the different soils equally, that the productivity of plants in loamy soil was observed to be greater as compared to plants of other soil samples. Clay soil plants showed improvements as compared to sand and silt soil, although not as good as loam. The worst growing plants were observed in sandy soil. This shows that the growth of Triticum aestivum plants is better in loamy soil, and loamy soil is the most beneficial for wheat crop productivity.