Open Innovation for Environmental Research

Innovation plays a key role in driving industries to gain competitive advantage. Increasingly, open innovation is considered a key driver to help industries accelerate the rate of innovation through exploitation of the free flow of internal and external knowledge and expertise. It is believed that industries will thus acquire stronger capability for innovation given the external input of expertise and knowledge that complements their internal capabilities. As a result, such businesses can achieve higher industrial competitiveness than those which rely only on traditional closed innovation approach. University-industry collaboration can be considered as a form of open innovation. Industries, especially small and medium enterprises, are particularly interested in partnering with universities as niche collaborators due to their innovation competence. In face of intensive competition from other neighboring cities in China like Shenzhen, Shanghai and Beijing, and neighboring countries like Singapore, Hong Kong has increasingly attempted to achieve economic competitiveness through innovation. University-industry collaboration has been increasingly advocated by the government as an effective means for innovation, such as the development and commercialization of niche technologies for the environment. In 2009-2010, Hong Kong ranked third in Global Innovation Index, out of 132 economies surveyed. In terms of university-industry collaboration, Hong Kong ranked twenty-seven. To gain a deeper understanding of what determines industry-university innovation, this study focusses on all cleaner energy and environmental-oriented Innovation-and-Technology (ITF) funded projects that have been approved since the establishment of Hong Kong Innovation and Technology Fund in 1999 and that have involved university-industry collaboration. A total of 145 out of 2,345 ITF funded projects that carry the theme of cleaner energy and environment research and development during 1999-2010 have been selected. Quantitative surveys and qualitative face-to-face interviews have been conducted to identify what drivers and barriers for this group of ITF industries are involved in their engagement in industry university collaboration, and why these drivers and barriers exist. The result obtained shows that majority of the local industries surveyed and interviewed are eager to collaborate with universities in environmental innovation for competitive advantage, especially for gaining reputations and securing future business opportunities. However, huge obstacles exist for local industries to partner with universities, especially for the SMEs, due to policy and institutional constraints. Innovation policies in support of SME innovation and institutional mechanisms to help SMEs find the right university partners are particularly relevant and critical for promoting open innovation (in the form of university-industry collaboration) in environmental and cleaner energy research among local industries in future.published_or_final_versio

Emergent quantum Euler equation and Bose-Einstein condensates

In this paper, proceeding from the recently developed way of deriving the quantum-mechanical equations from the classical ones, the complete system of hydrodynamical equations, including the quantum Euler equation, is derived for a perfect fluid and an imperfect fluid with pairwise interaction between the particles. For the Bose-Einstein condensate of the latter one the Bogolyubov spectrum of elementary excitations is easily reproduced in the acoustic approximation.Comment: 10 page

Predicting Auction Price of Vehicle License Plate with Deep Residual Learning

Due to superstition, license plates with desirable combinations of characters are highly sought after in China, fetching prices that can reach into the millions in government-held auctions. Despite the high stakes involved, there has been essentially no attempt to provide price estimates for license plates. We present an end-to-end neural network model that simultaneously predict the auction price, gives the distribution of prices and produces latent feature vectors. While both types of neural network architectures we consider outperform simpler machine learning methods, convolutional networks outperform recurrent networks for comparable training time or model complexity. The resulting model powers our online price estimator and search engine

Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT.

PURPOSE: Kilovoltage intrafraction monitoring (KIM) is a real-time 3D tumor monitoring system for cancer radiotherapy. KIM uses the commonly available gantry-mounted x-ray imager as input, making this method potentially more widely available than dedicated real-time 3D tumor monitoring systems. KIM is being piloted in a clinical trial for prostate cancer patients treated with VMAT (NCT01742403). The purpose of this work was to develop clinical process and quality assurance (QA) practices for the clinical implementation of KIM. METHODS: Informed by and adapting existing guideline documents from other real-time monitoring systems, KIM-specific QA practices were developed. The following five KIM-specific QA tests were included: (1) static localization accuracy, (2) dynamic localization accuracy, (3) treatment interruption accuracy, (4) latency measurement, and (5) clinical conditions accuracy. Tests (1)-(4) were performed using KIM to measure static and representative patient-derived prostate motion trajectories using a 3D programmable motion stage supporting an anthropomorphic phantom with implanted gold markers to represent the clinical treatment scenario. The threshold for system tolerable latency is <1 s. The tolerances for all other tests are that both the mean and standard deviation of the difference between the programmed trajectory and the measured data are <1 mm. The (5) clinical conditions accuracy test compared the KIM measured positions with those measured by kV/megavoltage (MV) triangulation from five treatment fractions acquired in a previous pilot study. RESULTS: For the (1) static localization, (2) dynamic localization, and (3) treatment interruption accuracy tests, the mean and standard deviation of the difference are <1.0 mm. (4) The measured latency is 350 ms. (5) For the tests with previously acquired patient data, the mean and standard deviation of the difference between KIM and kV/MV triangulation are <1.0 mm. CONCLUSIONS: Clinical process and QA practices for the safe clinical implementation of KIM, a novel real-time monitoring system using commonly available equipment, have been developed and implemented for prostate cancer VMAT

Determining appropriate imaging parameters for kilovoltage intrafraction monitoring: an experimental phantom study.

Kilovoltage intrafraction monitoring (KIM) utilises the kV imager during treatment for real-time tracking of prostate fiducial markers. However, its effectiveness relies on sufficient image quality for the fiducial tracking task. To guide the performance characterisation of KIM under different clinically relevant conditions, the effect of different kV parameters and patient size on image quality, and quantification of MV scatter from the patient to the kV detector panel were investigated in this study. Image quality was determined for a range of kV acquisition frame rates, kV exposure, MV dose rates and patient sizes. Two methods were used to determine image quality; the ratio of kV signal through the patient to the MV scatter from the patient incident on the kilovoltage detector, and the signal-to-noise ratio (SNR). The effect of patient size and frame rate on MV scatter was evaluated in a homogeneous CIRS pelvis phantom and marker segmentation was determined utilising the Rando phantom with embedded markers. MV scatter incident on the detector was shown to be dependent on patient thickness and frame rate. The segmentation code was shown to be successful for all frame rates above 3 Hz for the Rando phantom corresponding to a kV to MV ratio of 0.16 and an SNR of 1.67. For a maximum patient dimension less than 36.4 cm the conservative kV parameters of 5 Hz at 1 mAs can be used to reduce dose while retaining image quality, where the current baseline kV parameters of 10 Hz at 1 mAs is shown to be adequate for marker segmentation up to a patient dimension of 40 cm. In conclusion, the MV scatter component of image quality noise for KIM has been quantified. For most prostate patients, use of KIM with 10 Hz imaging at 1 mAs is adequate however image quality can be maintained and imaging dose reduced by altering existing acquisition parameters

Determining appropriate imaging parameters for kilovoltage intrafraction monitoring: an experimental phantom study.

Kilovoltage intrafraction monitoring (KIM) utilises the kV imager during treatment for real-time tracking of prostate fiducial markers. However, its effectiveness relies on sufficient image quality for the fiducial tracking task. To guide the performance characterisation of KIM under different clinically relevant conditions, the effect of different kV parameters and patient size on image quality, and quantification of MV scatter from the patient to the kV detector panel were investigated in this study. Image quality was determined for a range of kV acquisition frame rates, kV exposure, MV dose rates and patient sizes. Two methods were used to determine image quality; the ratio of kV signal through the patient to the MV scatter from the patient incident on the kilovoltage detector, and the signal-to-noise ratio (SNR). The effect of patient size and frame rate on MV scatter was evaluated in a homogeneous CIRS pelvis phantom and marker segmentation was determined utilising the Rando phantom with embedded markers. MV scatter incident on the detector was shown to be dependent on patient thickness and frame rate. The segmentation code was shown to be successful for all frame rates above 3 Hz for the Rando phantom corresponding to a kV to MV ratio of 0.16 and an SNR of 1.67. For a maximum patient dimension less than 36.4 cm the conservative kV parameters of 5 Hz at 1 mAs can be used to reduce dose while retaining image quality, where the current baseline kV parameters of 10 Hz at 1 mAs is shown to be adequate for marker segmentation up to a patient dimension of 40 cm. In conclusion, the MV scatter component of image quality noise for KIM has been quantified. For most prostate patients, use of KIM with 10 Hz imaging at 1 mAs is adequate however image quality can be maintained and imaging dose reduced by altering existing acquisition parameters

A nanoscale analysis method to reveal oxygen exchange between environment, oxide, and electrodes in ReRAM devices

The limited sensitivity of existing analysis techniques at the nanometer scale makes it challenging to systematically examine the complex interactions in redox-based resistive random access memory (ReRAM) devices. To test models of oxygen movement in ReRAM devices beyond what has previously been possible, we present a new nanoscale analysis method. Harnessing the power of secondary ion mass spectrometry, the most sensitive surface analysis technique, for the first time, we observe the movement of 16O across electrically biased SiOx ReRAM stacks. We can therefore measure bulk concentration changes in a continuous profile with unprecedented sensitivity. This reveals the nanoscale details of the reversible field-driven exchange of oxygen across the ReRAM stack. Both the reservoir-like behavior of a Mo electrode and the injection of oxygen into the surface of SiOx from the ambient are observed within one profile. The injection of oxygen is controllable through changing the porosity of the SiOx layer. Modeling of the electric fields in the ReRAM stacks is carried out which, for the first time, uses real measurements of both the interface roughness and electrode porosity. This supports our findings helping to explain how and where oxygen from ambient moisture enters devices during operation

Probing the Heterogeneity of Protein Kinase Activation in Cells by Super-Resolution Microscopy

Heterogeneity of mitogen-activated protein kinase (MAPK) activation in genetically identical cells, which occurs in response to epidermal growth factor receptor (EGFR) signaling, remains poorly understood. MAPK cascades integrate signals emanating from different EGFR spatial locations, including the plasma membrane and endocytic compartment. We previously hypothesized that in EGF-stimulated cells the MAPK phosphorylation (pMAPK) level and activity are largely determined by the spatial organization of the EGFR clusters within the cell. For experimental testing of this hypothesis, we used super-resolution microscopy to define EGFR clusters by receptor numbers (N) and average intra-cluster distances (d). From this data, we predicted the extent of pMAPK with 85% accuracy on a cell-to-cell basis with control data returning 54% accuracy (P50nm were most predictive for pMAPK level in cells. Electron microscopy revealed that these large clusters were primarily localized to the limiting membrane of multivesicular bodies (MVB). Many tighter packed dimers/multimers (d<50nm) were found on intraluminal vesicles within MVBs, where they were unlikely to activate MAPK because of the physical separation. Our results suggest that cell-to-cell differences in N and d contain crucial information to predict EGFR-activated cellular pMAPK levels and explain pMAPK heterogeneity in isogenic cells