University of Arkansas

About: University of Arkansas is a education organization based out in Fayetteville, Arkansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 17225 authors who have published 33329 publications receiving 941102 citations. The organization is also known as: Arkansas & UA.

One Fungus, One Name: Defining the Genus Fusarium in a Scientifically Robust Way That Preserves Longstanding Use

Abstract: In this letter, we advocate recognizing the genus Fusarium as the sole name for a group that includes virtually all Fusarium species of importance in plant pathology, mycotoxicology, medicine, and basic research. This phylogenetically guided circumscription will free scientists from any obligation to use other genus names, including teleomorphs, for species nested within this clade, and preserve the application of the name Fusarium in the way it has been used for almost a century. Due to recent changes in the International Code of Nomenclature for algae, fungi, and plants, this is an urgent matter that requires community attention. The alternative is to break the longstanding concept of Fusarium into nine or more genera, and remove important taxa such as those in the F. solani species complex from the genus, a move we believe is unnecessary. Here we present taxonomic and nomenclatural proposals that will preserve established research connections and facilitate communication within and between research communities, and at the same time support strong scientific principles and good taxonomic practice.

Solubility and emulsifying properties of soy protein isolates modified by pancreatin

Abstract: Soy protein isolates (SPI) with varying degrees of hydrolysis (DH of 7, 11, 15, 17%) were produced using pancreatin. The surface hydrophobicity indices of pancreatin hydrolyzed SPI (PSPI) (34.5, 34.9, 39. 1, and 40.7 for 7, 11, 15, 17% DH, respectively) were higher than that of SPI (10.5) and control SPI (CSPI) (12.5, 11.9, 12.9, and 12.6 for 10, 60, 120, and 180 min incubation, respectively). The solubilities of PSPI at pH 4.5 were 2.7, 9.1, 11.9, and 18.7%, for 7, 11, 15, and 17% DH, respectively, while the solubilities of SPI and CSPI at the same pH were about 1. 6%. Solubilities of PSPI at pH 7. 0 were > 90% for all DHs tested, while those of SPI and CSPI were 85%. The emulsifying activity index (EAI) of PSPI increased with increasing DH. PSPI with 15% DH had highest EAI (1. 122) which was higher (P < 0. 05) than those of SPI (0.550) and CSPI after 120 min incubation without enzyme (0.568). These results suggest that PSPI could be used as an ingredient for emulsified products and where high solubility at low pH is required.

Differential privacy preservation for deep auto-encoders: an application of human behavior prediction

Abstract: In recent years, deep learning has spread beyond both academia and industry with many exciting real-world applications. The development of deep learning has presented obvious privacy issues. However, there has been lack of scientific study about privacy preservation in deep learning. In this paper, we concentrate on the auto-encoder, a fundamental component in deep learning, and propose the deep private auto-encoder (dPA). Our main idea is to enforce e-differential privacy by perturbing the objective functions of the traditional deep auto-encoder, rather than its results. We apply the dPA to human behavior prediction in a health social network. Theoretical analysis and thorough experimental evaluations show that the dPA is highly effective and efficient, and it significantly outperforms existing solutions.