Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

3D QSAR analysis of oxazolidinone antibacterials: can we predict?

Three-dimensional QSAR studies for substituted aryloxazolidinones 3–9 were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus and Enterococcus faecalis exhibited a good correlation with the prediction made by the model using heat of formation and LUMO energies.

Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

Unravelling the self-assembly of hydrogen bonded NDI semiconductors in 2D and 3D

Supramolecular ordering of organic semiconductors is the key factor defining their electrical characteristics. Yet, it is extremely difficult to control, particularly at the interface with metal and dielectric surfaces in semiconducting devices. We have explored the growth of n-type semiconducting films based on hydrogen-bonded monoalkylnaphthalenediimide (NDI-R) from solution and through vapor deposition on both conductive and insulating surfaces. We combined scanning tunneling and atomic force microscopies with X-ray diffraction analysis to characterize, at the submolecular level, the evolution of the NDI-R molecular packing in going from monolayers to thin films. On a conducting (graphite) surface, the first monolayer of NDI-R molecules adsorbs in a flat-lying (face-on) geometry, whereas in subsequent layers the molecules pack edge-on in islands (Stranski–Krastanov-like growth). On SiO2, the NDI-R molecules form into islands comprising edge-on packed molecules (Volmer–Weber mode). Under all the explored conditions, self-complementary H bonding of the imide groups dictates the molecular assembly. The measured electron mobility of the resulting films is similar to that of dialkylated NDI molecules without H bonding. The work emphasizes the importance of H bonding interactions for controlling the ordering of organic semiconductors, and demonstrates a connection between on-surface self-assembly and the structural parameters of thin films used in electronic devices.

3D Fe2(MoO4)3 microspheres with nanosheet constituents as high-capacity anode materials for lithium-ion batteries

Three-dimensional (3D) Fe2(MoO4)3 microspheres with ultrathin nanosheet constituents are first synthesized as anode materials for the lithium-ion battery. It is interesting that the single-crystalline nanosheets allow rapid electron/ion transport on the inside, and the high porosity ensures fast diffusion of liquid electrolyte in energy storage applications. The electrochemical properties of Fe2(MoO4)3 as anode demonstrates that 3D Fe2(MoO4)3 microspheres deliver an initial capacity of 1855 mAh/g at a current density of 100 mA/g. Particularly, when the current density is increased to 800 mA/g, the reversible capacity of Fe2(MoO4)3 anode still arrived at 456 mAh/g over 50 cycles. The large and reversible capacities and stable charge–discharge cycling performance indicate that Fe2(MoO4)3 is a promising anode material for lithium battery applications. Graphical abstract The electrochemical properties of Fe2(MoO4)3 as anode demonstrates that 3D Fe2(MoO4)3 microspheres delivered an initial capacity of 1855 mAh/g at a current density of 100 mA/g. When the current density was increased to 800 mA/g, the Fe2(MoO4)3 still behaved high reversible capacity and good cycle performance.

3D hierarchical rutile TiO2 and metal-free organic sensitizer producing dye-sensitized solar cells 8.6% conversion efficiency

Three-dimensional (3D) hierarchical nanoscale architectures comprised of building blocks, with specifically engineered morphologies, are expected to play important roles in the fabrication of 'next generation' microelectronic and optoelectronic devices due to their high surface-to-volume ratio as well as opto-electronic properties. Herein, a series of well-defined 3D hierarchical rutile TiO2 architectures (HRT) were successfully prepared using a facile hydrothermal method without any surfactant or template, simply by changing the concentration of hydrochloric acid used in the synthesis. The production of these materials provides, to the best of our knowledge, the first identified example of a ledgewise growth mechanism in a rutile TiO2 structure. Also for the first time, a Dye-sensitized Solar Cell (DSC) combining a HRT is reported in conjunction with a high-extinction-coefficient metal-free organic sensitizer (D149), achieving a conversion efficiency of 5.5%, which is superior to ones employing P25 (4.5%), comparable to state-of-the-art commercial transparent titania anatase paste (5.8%). Further to this, an overall conversion efficiency 8.6% was achieved when HRT was used as the light scattering layer, a considerable improvement over the commercial transparent/reflector titania anatase paste (7.6%), a significantly smaller gap in performance than has been seen previously.

Rational design of 3D dendritic TiO2 nanostructures with favorable architectures

Controlling the morphology and size of titanium dioxide (TiO2) nanostructures is crucial to obtain superior photocatalytic, photovoltaic, and electrochemical properties. However, the synthetic techniques for preparing such structures, especially those with complex configurations, still remain a challenge because of the rapid hydrolysis of Ti-containing polymer precursors in aqueous solution. Herein, we report a completely novel approach-three- dimensional (3D) TiO2 nanostructures with favorable dendritic architectures-through a simple hydrothermal synthesis. The size of the 3D TiO2 dendrites and the morphology of the constituent nano-units, in the form of nanorods, nanoribbons, and nanowires, are controlled by adjusting the precursor hydrolysis rate and the surfactant aggregation. These novel configurations of TiO2 nanostructures possess higher surface area and superior electrochemical properties compared to nanoparticles with smooth surfaces. Our findings provide an effective solution for the synthesis of complex TiO2 nano-architectures, which can pave the way to further improve the energy storage and energy conversion efficiency of TiO 2-based devices.

Additively manufactured device for dynamic culture of large arrays of 3D tissue engineered constructs

The ability to test large arrays of cell and biomaterial combinations in 3D environments is still rather limited in the context of tissue engineering and regenerative medicine. This limitation can be generally addressed by employing highly automated and reproducible methodologies. This study reports on the development of a highly versatile and upscalable method based on additive manufacturing for the fabrication of arrays of scaffolds, which are enclosed into individualized perfusion chambers. Devices containing eight scaffolds and their corresponding bioreactor chambers are simultaneously fabricated utilizing a dual extrusion additive manufacturing system. To demonstrate the versatility of the concept, the scaffolds, while enclosed into the device, are subsequently surface-coated with a biomimetic calcium phosphate layer by perfusion with simulated body fluid solution. 96 scaffolds are simultaneously seeded and cultured with human osteoblasts under highly controlled bidirectional perfusion dynamic conditions over 4 weeks. Both coated and noncoated resulting scaffolds show homogeneous cell distribution and high cell viability throughout the 4 weeks culture period and CaP-coated scaffolds result in a significantly increased cell number. The methodology developed in this work exemplifies the applicability of additive manufacturing as a tool for further automation of studies in the field of tissue engineering and regenerative medicine.

A 3D in vitro model reflecting the androgen deprivation state in prostate cancer bone metastasis

In castrate-resistant prostate cancer (CRPC), the prevailing organ for metastasis is bone, where the survival of cancer cells is regulated by the permissive metastatic niche offered by the bone marrow. The tumour microenvironment and cellular interactions with the matrix and bone cells enable metastasis and lead to cancer cells becoming androgen resistant. Hence, 3D models that mimic CRPC in terms of an androgen deprivation state (ADS) are needed to identify the mechanisms for CPRC growth in bone and further develop therapeutic strategies.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

Cultures of sharing in 3D printing: What can we learn from the licence choices of Thingiverse users?

This article contributes to the discussion by analysing how users of the leading online 3D printing design repository Thingiverse manage their intellectual property (IP). 3D printing represents a fruitful case study for exploring the relationship between IP norms and practitioner culture. Although additive manufacturing technology has existed for decades, 3D printing is on the cusp of a breakout into the technological mainstream – hardware prices are falling; designs are circulating widely; consumer-friendly platforms are multiplying; and technological literacy is rising. Analysing metadata from more than 68,000 Thingiverse design files collected from the site, we examine the licensing choices made by users and explore the way this shapes the sharing practices of the site’s users. We also consider how these choices and practices connect with wider attitudes towards sharing and intellectual property in 3D printing communities. A particular focus of the article is how Thingiverse structures its regulatory framework to avoid IP liability, and the extent to which this may have a bearing on users’ conduct. The paper has three sections. First, we will offer a description of Thingiverse and how it operates in the 3D printing ecosystem, noting the legal issues that have arisen regarding Thingiverse’s Terms of Use and its allocation of intellectual property rights. Different types of Thingiverse licences will be detailed and explained. Second, the empirical metadata we have collected from Thingiverse will be presented, including the methods used to obtain this information. Third, we will present findings from this data on licence choice and the public availability of user designs. Fourth, we will look at the implications of these findings and our conclusions regarding the particular kind of sharing ethic that is present in Thingiverse; we also consider the “closed” aspects of this community and what this means for current debates about “open” innovation.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

3D extracellular matrix interactions modulate tumour cell growth, invasion and angiogenesis in engineered tumour microenvironments

Interactions between tumour cells and extracellular matrix proteins of the tumour microenvironment play crucial roles in cancer progression. So far, however, there are only a few experimental platforms available that allow us to study these interactions systematically in a mechanically defined three-dimensional (3D) context. Here, we have studied the effect of integrin binding motifs found within common extracellular matrix (ECM) proteins on 3D breast (MCF-7) and prostate (PC-3, LNCaP) cancer cell cultures, and co-cultures with endothelial and mesenchymal stromal cells. For this purpose, matrix metalloproteinase-degradable biohybrid poly(ethylene) glycol-heparin hydrogels were decorated with the peptide motifs RGD, GFOGER (collagen I), or IKVAV (laminin-111). Over 14 days, cancer spheroids of 100-200µm formed. While the morphology of poorly invasive MCF-7 and LNCaP cells was not modulated by any of the peptide motifs, the aggressive PC-3 cells exhibited an invasive morphology when cultured in hydrogels comprising IKVAV and GFOGER motifs compared to RGD motifs or nonfunctionalised controls. PC-3 (but not MCF-7 and LNCaP) cell growth and endothelial cell infiltration were also significantly enhanced in IKVAV and GFOGER presenting gels. Taken together, we have established a 3D culture model that allows for dissecting the effect of biochemical cues on processes relevant to early cancer progression. These findings provide a basis for more mechanistic studies that may further advance our understanding of how ECM modulates cancer cell invasion and how to ultimately interfere with this process.

A model based factorization approach for dense 3D recovery from monocular video

Feature track matrix factorization based methods have been attractive solutions to the Structure-front-motion (Sfnl) problem. Group motion of the feature points is analyzed to get the 3D information. It is well known that the factorization formulations give rise to rank deficient system of equations. Even when enough constraints exist, the extracted models are sparse due the unavailability of pixel level tracks. Pixel level tracking of 3D surfaces is a difficult problem, particularly when the surface has very little texture as in a human face. Only sparsely located feature points can be tracked and tracking error arc inevitable along rotating lose texture surfaces. However, the 3D models of an object class lie in a subspace of the set of all possible 3D models. We propose a novel solution to the Structure-from-motion problem which utilizes the high-resolution 3D obtained from range scanner to compute a basis for this desired subspace. Adding subspace constraints during factorization also facilitates removal of tracking noise which causes distortions outside the subspace. We demonstrate the effectiveness of our formulation by extracting dense 3D structure of a human face and comparing it with a well known Structure-front-motion algorithm due to Brand.