Clemson University

About: Clemson University is a education organization based out in Clemson, South Carolina, United States. It is known for research contribution in the topics: Population & Control theory. The organization has 20556 authors who have published 42518 publications receiving 1170779 citations. The organization is also known as: Clemson Agricultural College of South Carolina.

Nanobiotechnology can boost crop production and quality: first evidence from increased plant biomass, fruit yield and phytomedicine content in bitter melon (Momordica charantia)

Abstract: Recent research on nanoparticles in a number of crops has evidenced for enhanced germination and seedling growth, physiological activities including photosynthetic activity and nitrogen metabolism, mRNA expression and protein level, and also positive changes in gene expression indicating their potential use in crop improvement. We used a medicinally rich vegetable crop, bitter melon, as a model to evaluate the effects of seed treatment with a carbon-based nanoparticle, fullerol [C60(OH)20], on yield of plant biomass and fruit characters, and phytomedicine contents in fruits. We confirmed the uptake, translocation and accumulation of fullerol through bright field imaging and Fourier transform infra-red spectroscopy. We observed varied effects of seed treatment at five concentrations, including non-consequential and positive, on plant biomass yield, fruit yield and its component characters, and content of five phytomedicines in fruits. Fullerol-treatment resulted in increases up to 54% in biomass yield and 24% in water content. Increases of up to 20% in fruit length, 59% in fruit number, and 70% in fruit weight led to an improvement up to 128% in fruit yield. Contents of two anticancer phytomedicines, cucurbitacin-B and lycopene, were enhanced up to 74% and 82%, respectively, and contents of two antidiabetic phytomedicines, charantin and insulin, were augmented up to 20% and 91%, respectively. Non-significant correlation inter se plant biomass, fruit yield, phytomedicine content and water content evidenced for separate genetic control and biosynthetic pathways for production of plant biomass, fruits, and phytomedicines in fruits, and also no impact of increased water uptake. While our results indicated possibility of improving crop yield and quality by using proper concentrations of fullerol, extreme caution needs to be exercised given emerging knowledge about accumulation and toxicity of nanoparticles in bodily tissues.

Degradable natural polymer hydrogels for articular cartilage tissue engineering

Abstract: Articular cartilage has poor ability to heal once damaged. Tissue engineering with scaffolds of polymer hydrogels is promising for cartilage regeneration and repair. Polymer hydrogels composed of highly hydrated crosslinked networks mimic the collagen networks of the cartilage extracellular matrix and thus are employed as inserts at cartilage defects not only to temporarily relieve the pain but also to support chondrocyte proliferation and neocartilage regeneration. The biocompatibility, biofunctionality, mechanical properties, and degradation of the polymer hydrogels are the most important parameters for hydrogel-based cartilage tissue engineering. Degradable biopolymers with natural origin have been widely used as biomaterials for tissue engineering because of their outstanding biocompatibility, low immunological response, low cytotoxicity, and excellent capability to promote cell adhesion, proliferation, and regeneration of new tissues. This review covers several important natural proteins (collagen, gelatin, fibroin, and fibrin) and polysaccharides (chitosan, hyaluronan, alginate and agarose) widely used as hydrogels for articular cartilage tissue engineering. The mechanical properties, structures, modification, and structure–performance relationship of these hydrogels are discussed since the chemical structures and physical properties dictate the in vivo performance and applications of polymer hydrogels for articular cartilage regeneration and repair. © 2012 Society of Chemical Industry

Precision and accuracy of single-molecule FRET measurements—a multi-laboratory benchmark study

Abstract: Single-molecule Forster resonance energy transfer (smFRET) is increasingly being used to determine distances, structures, and dynamics of biomolecules in vitro and in vivo. However, generalized protocols and FRET standards to ensure the reproducibility and accuracy of measurements of FRET efficiencies are currently lacking. Here we report the results of a comparative blind study in which 20 labs determined the FRET efficiencies (E) of several dye-labeled DNA duplexes. Using a unified, straightforward method, we obtained FRET efficiencies with s.d. between ±0.02 and ±0.05. We suggest experimental and computational procedures for converting FRET efficiencies into accurate distances, and discuss potential uncertainties in the experiment and the modeling. Our quantitative assessment of the reproducibility of intensity-based smFRET measurements and a unified correction procedure represents an important step toward the validation of distance networks, with the ultimate aim of achieving reliable structural models of biomolecular systems by smFRET-based hybrid methods.

FoldingNet: Point Cloud Auto-encoder via Deep Grid Deformation

Abstract: Recent deep networks that directly handle points in a point set, e.g., PointNet, have been state-of-the-art for supervised learning tasks on point clouds such as classification and segmentation. In this work, a novel end-to-end deep auto-encoder is proposed to address unsupervised learning challenges on point clouds. On the encoder side, a graph-based enhancement is enforced to promote local structures on top of PointNet. Then, a novel folding-based decoder deforms a canonical 2D grid onto the underlying 3D object surface of a point cloud, achieving low reconstruction errors even for objects with delicate structures. The proposed decoder only uses about 7% parameters of a decoder with fully-connected neural networks, yet leads to a more discriminative representation that achieves higher linear SVM classification accuracy than the benchmark. In addition, the proposed decoder structure is shown, in theory, to be a generic architecture that is able to reconstruct an arbitrary point cloud from a 2D grid. Our code is available at this http URL

Nonlinear coupling control laws for an underactuated overhead crane system

Abstract: In this paper, we consider the regulation control problem for an underactuated overhead crane system. Motivated by recent passivity-based controllers for underactuated systems, we design several controllers that asymptotically regulate the planar gantry position and the payload angle. Specifically, utilizing LaSalle's invariant set theorem, we first illustrate how a simple proportional-derivative (PD) controller can be utilized to asymptotically regulate the overhead crane system. Motivated by the desire to achieve improved transient performance, we then present two nonlinear controllers that increase the coupling between the planar gantry position and the payload angle. Experimental results are provided to illustrate the improved performance of the nonlinear controllers over the simple PD controller.