UPGPT: Universal Diffusion Model for Person Image Generation, Editing and Pose Transfer

Existing person image generative models can do either image generation or pose transfer but not both. We propose a unified diffusion model, UPGPT to provide a universal solution to perform all the person image tasks - generative, pose transfer, and editing. With fine-grained multimodality and disentanglement capabilities, our approach offers fine-grained control over the generation and the editing process of images using a combination of pose, text, and image, all without needing a semantic segmentation mask which can be challenging to obtain or edit. We also pioneer the parameterized body SMPL model in pose-guided person image generation to demonstrate new capability - simultaneous pose and camera view interpolation while maintaining a person's appearance. Results on the benchmark DeepFashion dataset show that UPGPT is the new state-of-the-art while simultaneously pioneering new capabilities of edit and pose transfer in human image generation

Data mining of portable EEG brain wave signals for sports performance analysis: An Archery case study

BACKGROUND ♦ Achievement in high performance sport requires an appropriate ‘state of mind’, which is trained alongside the physical skills. ♦ However, quantification of mental state during coaching is often difficult. ♦ With the advent of a new generation of portable compact EEGs and wireless eye tracking devices, one can measure the neurocognitive activity of an athlete’s brain and their visual focus simultaneously in ecologically representative training scenarios. AIM/OBJECTIVES ♦ We present evidence suggesting that the ‘state of mind’ of an athlete can be measured and compared with target-based performance measures. METHOD ♦ Measurements were taken from intermediate, county level, near elite and elite archers investigating: o quantification of EEG brain wave signals comparing archers of different abilities o correlation of EEG data across shots as a function of marksmanship o prototyping real-time EEG data feedback using sound during training o synchronous EEG and eye tracking ♦ Archery was chosen to demonstrate the real-time and in-situ quantification of neural activity compared with target-based measures of performance that archery provides, over a range of timespans and skills. ♦ Mental performance was explored during stages of a shot, across shots within a set, or across different sessions. RESULTS ♦ Results demonstrate that there are significant and measurable changes in EEG patterns during a shot with evidence suggesting that the patterns vary as a function of skill level, but not simply as a function of score. ♦ Significance of each of these outcomes for goal-directed learning and performance enhancement are discussed. DISCUSSION ♦ This may provide coaches and athletes with real-time EEG feedback to identify differing mental skill execution compared to a baseline or aspirational measurement from another athlete. ♦ Future work includes injury recovery/prevention and welfare, rehabilitation, and work with mobility-challenged non-athletes

Mirror Symmetry is T-Duality

It is argued that every Calabi-Yau manifold $X$ with a mirror $Y$ admits a family of supersymmetric toroidal 3-cycles. Moreover the moduli space of such cycles together with their flat connections is precisely the space $Y$. The mirror transformation is equivalent to T-duality on the 3-cycles. The geometry of moduli space is addressed in a general framework. Several examples are discussed.Comment: 20 pages, harvmac -- some references added, typos correcte

Symplectic Floer homology of area-preserving surface diffeomorphisms

The symplectic Floer homology HF_*(f) of a symplectomorphism f:S->S encodes data about the fixed points of f using counts of holomorphic cylinders in R x M_f, where M_f is the mapping torus of f. We give an algorithm to compute HF_*(f) for f a surface symplectomorphism in a pseudo-Anosov or reducible mapping class, completing the computation of Seidel's HF_*(h) for h any orientation-preserving mapping class.Comment: 57 pages, 4 figures. Revision for publication, with various minor corrections. Adds results on the module structure and invariance thereo

Del Pezzo surfaces with many symmetries

We classify smooth del Pezzo surfaces whose alpha-invariant of Tian is bigger than one.Comment: 23 page

Principal-component-based multivariate regression for genetic association studies of metabolic syndrome components

<p>Abstract</p> <p>Background</p> <p>Quantitative traits often underlie risk for complex diseases. For example, weight and body mass index (BMI) underlie the human abdominal obesity-metabolic syndrome. Many attempts have been made to identify quantitative trait loci (QTL) over the past decade, including association studies. However, a single QTL is often capable of affecting multiple traits, a quality known as gene pleiotropy. Gene pleiotropy may therefore cause a loss of power in association studies focused only on a single trait, whether based on single or multiple markers.</p> <p>Results</p> <p>We propose using principal-component-based multivariate regression (PCBMR) to test for gene pleiotropy with comprehensive evaluation. This method generates one or more independent canonical variables based on the principal components of original traits and conducts a multivariate regression to test for association with these new variables. Systematic simulation studies have shown that PCBMR has great power. PCBMR-based pleiotropic association studies of abdominal obesity-metabolic syndrome and its possible linkage to chromosomal band 3q27 identified 11 susceptibility genes with significant associations. Whereas some of these genes had been previously reported to be associated with metabolic traits, others had never been identified as metabolism-associated genes.</p> <p>Conclusions</p> <p>PCBMR is a computationally efficient and powerful test for gene pleiotropy. Application of PCBMR to abdominal obesity-metabolic syndrome indicated the existence of gene pleiotropy affecting this syndrome.</p

Cognitive and disease-modifying effects of 11ß-hydroxysteroid dehydrogenase type 1 inhibition in male Tg2576 mice, a model of Alzheimer's disease

Chronic exposure to elevated levels of glucocorticoids has been linked to age-related cognitive decline and may play a role in Alzheimer's disease. In the brain, 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) amplifies intracellular glucocorticoid levels. We show that short-term treatment of aged, cognitively impaired C57BL/6 mice with the potent and selective 11β-HSD1 inhibitor UE2316 improves memory, including after intracerebroventricular drug administration to the central nervous system alone. In the Tg2576 mouse model of Alzheimer's disease, UE2316 treatment of mice aged 14 months for 4 weeks also decreased the number of β-amyloid (Aβ) plaques in the cerebral cortex, associated with a selective increase in local insulin-degrading enzyme (involved in Aβ breakdown and known to be glucocorticoid regulated). Chronic treatment of young Tg2576 mice with UE2316 for up to 13 months prevented cognitive decline but did not prevent Aβ plaque formation. We conclude that reducing glucocorticoid regeneration in the brain improves cognition independently of reduced Aβ plaque pathology and that 11β-HSD1 inhibitors have potential as cognitive enhancers in age-associated memory impairment and Alzheimer's dementia

Microscopic Origin of the Bekenstein-Hawking Entropy

The Bekenstein-Hawking area-entropy relation $S_{BH}=A/4$ is derived for a class of five-dimensional extremal black holes in string theory by counting the degeneracy of BPS soliton bound states.Comment: 12 pages. Relatively minor corrections and additions to discussio