Reference, context and propositions

This thesis is a detailed investigation of a web of philosophical problems surrounding what I call Kripke' s Thesis: if proper names are directly referential then such identity statements as 'Hesperus is Phosphorus', which are constructed from two distinct but co-referential proper names, are necessary and yet a posteriori. Chapter 1 clarifies some confusions surrounding Kripke's view about rigidity (rigid designation) and his theory of naming. Problems concerning the scope interpretation of rigidity, rigid descriptions, and Kaplan-rigidity are dealt with. My major claim is that the fundamental notion of Kripke's theory of naming is direct reference, not rigidity. In Chapter 2, I first establish the 'modal half of Kripke's Thesis. Then an objection against Kripke's Thesis is presented. The central claim of the objection is this: given that proper names are directly referential and that the proposition expressed by (e.g.) 'Hesperus is Hesperus' is a priori, 'Hesperus is Phosphorus' expresses the same proposition as 'Hesperus is Hesperus', and is therefore a priori. An attempt, based on a suggestion by Plantinga, to defend Kripke's Thesis is shown to be unsuccessful. In Chapter 3, it is first noted that the objection previously presented involves the assumption (T): 'a priori' applies primarily to propositions and derivatively to sentences. Then, on the basis of Stalnaker's semantic apparatus of propositional concepts, a two-dimensional account of a priority is developed. By rejecting (T) and embracing a sentence-relative view of 'a priori propositions', this account provides a defence of Kripke's Thesis. It is argued that this is not an ad hoc defence. In Chapter 4, attention turns to some problems concerning context dependence, a central feature of the two-dimensional account proposed in Chapter 3. Chapter 4 starts with the observation that the account seems to be committed to an indexical treatment of proper names. This prompts a demonstration of the compatibility of indexicality and rigidity. The demonstration, drawing on Kaplan's semantics for indexicals, introduces, however, the more serious problem of how to square the purported indexicality of proper names, as revealed by the two-dimensional account, with Kaplan's contention that proper names have a stable character. A solution which invokes the notion of frame relativity is proposed. The first section of Chapter 5 aims to clarify the intricate relation between 'singular propositions' and 'direct reference'. The rest of the chapter is a detailed analysis of Salmon's attempt to refute Kripke's Thesis. It is argued that Salmon's attempt fails, and that the source of his failure lies in his characterization of a priority. Some objections to this analysis are considered and rejected

SCNet: Learning Semantic Correspondence

This paper addresses the problem of establishing semantic correspondences between images depicting different instances of the same object or scene category. Previous approaches focus on either combining a spatial regularizer with hand-crafted features, or learning a correspondence model for appearance only. We propose instead a convolutional neural network architecture, called SCNet, for learning a geometrically plausible model for semantic correspondence. SCNet uses region proposals as matching primitives, and explicitly incorporates geometric consistency in its loss function. It is trained on image pairs obtained from the PASCAL VOC 2007 keypoint dataset, and a comparative evaluation on several standard benchmarks demonstrates that the proposed approach substantially outperforms both recent deep learning architectures and previous methods based on hand-crafted features.Comment: ICCV 201

DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by recent methods on text-guided 3D common object generation, generating high-quality human avatars remains an open challenge due to the complexity of the human body's shape, pose, and appearance. We propose DreamAvatar to tackle this challenge, which utilizes a trainable NeRF for predicting density and color for 3D points and pretrained text-to-image diffusion models for providing 2D self-supervision. Specifically, we leverage the SMPL model to provide shape and pose guidance for the generation. We introduce a dual-observation-space design that involves the joint optimization of a canonical space and a posed space that are related by a learnable deformation field. This facilitates the generation of more complete textures and geometry faithful to the target pose. We also jointly optimize the losses computed from the full body and from the zoomed-in 3D head to alleviate the common multi-face ''Janus'' problem and improve facial details in the generated avatars. Extensive evaluations demonstrate that DreamAvatar significantly outperforms existing methods, establishing a new state-of-the-art for text-and-shape guided 3D human avatar generation.Comment: Project page: https://yukangcao.github.io/DreamAvatar

Influence of the inlet air temperature on the microencapsulation of kenaf (Hibiscus cannabinus L.) seed oil.

The aim of this study was to evaluate the influence of different inlet air temperatures on the physicochemical properties and oxidative stability of microencapsulated kenaf seed oil (MKSO). Kenaf seed oil was homogenised with the wall materials at a total solid content of 30% and was spray-dried at 160, 180 or 200°C inlet air temperature. The microstructure and morphology of the microencapsulated kenaf seed oil were observed using a scanning electron microscope. The physicochemical properties, such as moisture content, water activity and particle size, of MKSO produced at different inlet air temperatures showed a significant difference (p<0.05). MKSO produced with an inlet air temperature of 160°C exhibited the highest microencapsulation efficiency (MEE, 96.46%) compared to 180°C (78.42%) and the efficiency was lowest at 200°C (58.96%). Increasing the inlet air temperature also resulted in significantly increased (p<0.05) lipid oxidation of MKSO and decreased total intrinsic phenolic content upon accelerated storage. However, all MKSO had lower lipid oxidation and higher total phenolic content than bulk (unencapsulated) oil. This study indicates that increased inlet air temperature results in larger particle size, higher lipid oxidation and lower MEE. The process of microencapsulation could protect oil from the external environment that causes lipid oxidation. Practical applications: Kenaf seed oil contains PUFA and phytosterols, which are beneficial to human health. However, the PUFA in kenaf seed oil is susceptible to lipid oxidation, which degrades its nutritional value. Microencapsulation is used to protect the kenaf seed oil from being oxidised. By knowing the influence of the inlet air temperature on the physical properties and oxidative stability of the microencapsulated kenaf seed oil, the ideal inlet air temperature can be used to produce microencapsulated kenaf seed oil, which may be incorporated into food products to supplement the bioactive compounds that are beneficial to human health

Protective actions of des-acylated ghrelin on brain injury and blood-brain barrier disruption after stroke in mice

The major ghrelin forms, acylated ghrelin and des-acylated ghrelin, are novel gastrointestinal hormones. Moreover, emerging evidence indicates that these peptides may have other functions including neuro- and vaso-protection. Here, we investigated whether post-stroke treatment with acylated ghrelin or des-acylated ghrelin could improve functional and histological endpoints of stroke outcome in mice after transient middle cerebral artery occlusion (tMCAo). We found that des-acylated ghrelin (1 mg/kg) improved neurological and functional performance, reduced infarct and swelling, and decreased apoptosis. In addition, it reduced blood-brain barrier (BBB) disruption in vivo and attenuated the hyper-permeability of mouse cerebral microvascular endothelial cells after oxygen glucose deprivation and reoxygenation (OGD + RO). By contrast, acylated ghrelin (1 mg/kg or 5 mg/kg) had no significant effect on these endpoints of stroke outcome. Next we found that des-acylated ghrelin's vasoprotective actions were associated with increased expression of tight junction proteins (occludin and claudin-5), and decreased cell death. Moreover, it attenuated superoxide production, Nox activity and expression of 3-nitrotyrosine. Collectively, these results demonstrate that post-stroke treatment with des-acylated ghrelin, but not acylated ghrelin, protects against ischaemia/reperfusion-induced brain injury and swelling, and BBB disruption, by reducing oxidative and/or nitrosative damage

HeadSculpt: Crafting 3D Head Avatars with Text

Recently, text-guided 3D generative methods have made remarkable advancements in producing high-quality textures and geometry, capitalizing on the proliferation of large vision-language and image diffusion models. However, existing methods still struggle to create high-fidelity 3D head avatars in two aspects: (1) They rely mostly on a pre-trained text-to-image diffusion model whilst missing the necessary 3D awareness and head priors. This makes them prone to inconsistency and geometric distortions in the generated avatars. (2) They fall short in fine-grained editing. This is primarily due to the inherited limitations from the pre-trained 2D image diffusion models, which become more pronounced when it comes to 3D head avatars. In this work, we address these challenges by introducing a versatile coarse-to-fine pipeline dubbed HeadSculpt for crafting (i.e., generating and editing) 3D head avatars from textual prompts. Specifically, we first equip the diffusion model with 3D awareness by leveraging landmark-based control and a learned textual embedding representing the back view appearance of heads, enabling 3D-consistent head avatar generations. We further propose a novel identity-aware editing score distillation strategy to optimize a textured mesh with a high-resolution differentiable rendering technique. This enables identity preservation while following the editing instruction. We showcase HeadSculpt's superior fidelity and editing capabilities through comprehensive experiments and comparisons with existing methods.Comment: Webpage: https://brandonhan.uk/HeadSculpt