A plants’ ability to withstand chilling and frost damage will dictate the geography in which production can occur. Global warming is predicted to increase chilling and frost injury in crops. It is important to note that frost injury is one of the key factors limiting production. In corn, chilling injury is an ongoing constraint for global production and expansion which affects food, feed and fuel supplies. Corn is an important model system as it is the largest crop, on a tonnage basis, produced in the world.

The most critical region for winter wheat (Triticum aestivum L.) winter survival is the crown. Exposure to different environmental cues during cold acclimation improves the crown’s resistance to freezing. This key fact is not taken into account in the design of controlled environment experiments and may not reflect actual mechanisms of cold hardiness in the field. Acclimation to multiple environmental cues under fall field conditions could explain the improved freezing survival of field as opposed to chamber acclimated plants.

Many problems which are best solved by neural networks are exhibiting rapid growth in nascent and existing fields, such as natural language processing, and image recognition for self-driving cars. Current limitations in manufacturing technologies impose limits that prevent these performance demands from being met through conventional methods. Neuromorphic computing has been proposed as a potential solution for problems best solved with artificial neural networks.

Circadian rhythms are processes which allows animals to regulate their physiology based on time of day. These rhythms are controlled by the circadian clock, a group of transcription factors that form a feedback loop. Over 40% of the genome is transcribed rhythmically, implicating the clock in many physiological processes. The cell cycle is another process which takes ~24h to complete in mammals. This is due to several checkpoints which are present to prevent the cell from precocious progression leading to DNA damage.

Improving the durability of superhydrophobic surfaces is of significant interest in the surface engineering community. We have recently developed a novel superhydrophobic coating with a hard nanocrystalline nickel matrix and embedded hydrophobic polytetrafluoroethylene (PTFE) particles. To further improve the mechanical robustness of the non-wetting coating, the soft polymeric PTFE particles were replaced with hard, hydrophobic cerium oxide ceramic particles. However, the intrinsic hydrophobic properties of cerium oxide are not well understood.

Recent natural disasters, such as the 2005 Hurricane Katrina and the 2011 Tohoku Tsunami, have increased focus on the resilient design of coastal communities to these devastating large-scale hydraulic events. The loads from these events can be separated into hydraulic and debris loads. Debris loads, in particular, are difficult to evaluate in the field and numerically, therefore generally are evaluated in an experimental setting. To this point, the focus of debris load research has been on single debris impacts on structures.

Parallel mechanisms/robots have been developed for numerous applications. At Ryerson University, it has been implemented in morphing wing mechanism design. However, an ideal morphing skin is required to create a functional morphing wing. In addition to morphing wings, other applications may require parallel robots to be covered due to environment requirements, for example, medical, industrial, and nuclear robots. These coverings can be classified as flexible and rigid. Flexible covers are stretchable materials.

Over the last few years, the data revolution occurred with the emergence of “Big data”. In medical field, the term big data refers to large databases in terms of patients and/or information from varied sources. Nevertheless, heterogeneity is encountered in this kind of data. Indeed, data arise from different medical centers. Furthermore, we can’t perform traditional statistical methods on these large databases: major problem are multicollinearity and overfitting. Lots of regularization methods have been proposed in order to adapt classical methods. Mittal et al.

Current UV technology used to disinfect drinking water and wastewater is energy intensive, hazardous, and bulky; and the advent of light emitting diodes (LEDs) that emit in the ultraviolet (UV) range provides a unique opportunity to rethink how we design and implement disinfection technology. The overall objective of this project is to investigate the how the arrangement of UV LEDs and the hydraulic conditions in a novel bench-scale flow through UV-LED reactor affect disinfection performance. The project will be carried out in two phases.

With the rising concern regarding environmental pollution and greenhouse gases, the demand for clean and renewable energy sources has never been greater. Recent developments in fuel cell technology have been promising; however, these fuel cells may be unsuited for mass production due to the prohibitive cost of the platinum-group metal nanoparticles which are required as electrocatalysts. Thus, there is a pressing need for improvements to fuel cell technology such that they require much less platinum metal.