The application of stainless steel (SS) as an alternative construction material has been developing in the last decade. SS construction has an outstanding structural performance, excellent corrosion resistance, and long-term durability. Moreover, the SS construction has a relatively low maintenance cost with possibility of a longer occupancy period, and thus it promotes sustainability in the construction industry. In combination with the cold-forming technique during the fabrication process, SS structures offer additional strength and a faster construction speed. However, the available international design standards for cold-formed stainless steel (CFSS) structures have not been developed thoroughly, specifically on the strength prediction of a member under concentrated bearing loads, which causes a web crippling. Therefore, a series of laboratory testing and computational simulations were conducted in this research to evaluate the existing design standards. The reliability analysis shows that the available strength predictions in the design standards are not safely used even though they are conservative. This research proposes new strength predictions that are safe and conservative, and it can be used for an improvement of the design standards.
Precision manipulation of various liquids is essential in many fields, including DNA analysis, proteomics, cell assay and clinical diagnosis, chemical synthesis, and drug discovery. Their divisible, sticky, and sometime infectious features impose, however, great challenges on processing them, particularly when their volume is down to nano-/subnano-liter. A blood droplet from an Ebola patient can for example infect medical workers through the skin. For diagnosis, medial workers have to crash, filter, and purify a patient’s blood sample to obtain the virus’s genetic materials. This series of operations, very often in a fluidic medium, is highly infectious. Moreover, fluids stick to surfaces, which will contaminate containers and handling tools, causing potential dangers if the medical wastes are not properly managed. In this talk, Prof. Wang shall demonstrate how a simple light or fiber touch functions as a “magic” wetting-proof hand to navigate, fuse, pinch, and cleave fluids on demand, being capable of reducing and even replacing the usage of disposable plastics in the biomedical and pharmaceutical industries.
In Hong Kong, the number of elderly citizens is estimated to rise to one third of the population, or 2.37 million, in year 2037. As they age and become more frail, the demand for formal support services (e.g., providing domestic or escort services) will increase significantly in the coming years. However, there is a severe lack of manpower to meet these needs. Some elderly-care homes reported a 70% shortage of employees. There is thus a strong need of voluntary or part-time helpers for taking care of elders.
In this talk, Prof. Cheng will introduce HINCare, a software platform that encourages mutual-help and volunteering culture in the community. HINCare uses the HIN (Heterogeneous Information Network) to recommend helpers to elders or other service recipients. The algorithms that use HINs and AI technologies for matching elders and helpers are based on our recent research results. This is the first time that HIN is used to support elderly care.
HINCare is now downloadable in Apple and Google Play Store, and has been serving more than a thousand of elders and helpers in NGOs (e.g., SKH and CSFC). The app is originally designed for elderly users, but has now expanded its services to support the Community Investment and Inclusion Fund (CIIF) and 10 NGOs engaged in teenage and family services. The system won the HKICT Award 2021, Asia Smart App Award 2020, and the HKU Faculty Knowledge Exchange Awards 2021 HKU.
In recent years, there has been a trend towards integrating small, soft and deformable structures into surgical robot systems. Target applications include endoscopy or magnetic resonance imaging (MRI)-guided intervention, where researchers take advantage of soft and flexible robots for their inherent mechanical compliance. However, these flexible robotic systems are often controlled in an open loop or with positional feedback from 3D tracking devices. Not only the real-time feedback of flexible/soft robot configuration or morphology itself is of importance, but also the robot manipulation modelling, as well as its intelligent control, become an area of interest in the field. To this end, this talk will present various robot prototypes, which attempt to resolve unmet clinical and technical challenges for image-guided intervention or surgery, either in strong magnetic field (1.5-3T) by magnetic resonance imaging (MRI) scanner or in confined anatomical space through endoscopy. Machine intelligent approaches, and also the recent advances in continuum robot design and learning-based sensing/control will also be overviewed. These robots have to incorporate with efficient mechanical transmission, thus enabling delicate mechanical force/motion transmitted from actuators to surgical tools in a long and flexible route. The ultimate goal is to provide high-performance control of robotics instruments for safe, precise and effective surgical manipulation. The speaker will not only share his research outcome, but also various difficulties in his up-and-down research journey, from R&D in university, (pre-)clinical trials in hospital, then technology transfer for clinical applications.