Unleashing the Imagination of Text: A Novel Framework for Text-to-image Person Retrieval via Exploring the Power of Words

The goal of Text-to-image person retrieval is to retrieve person images from a large gallery that match the given textual descriptions. The main challenge of this task lies in the significant differences in information representation between the visual and textual modalities. The textual modality conveys abstract and precise information through vocabulary and grammatical structures, while the visual modality conveys concrete and intuitive information through images. To fully leverage the expressive power of textual representations, it is essential to accurately map abstract textual descriptions to specific images. To address this issue, we propose a novel framework to Unleash the Imagination of Text (UIT) in text-to-image person retrieval, aiming to fully explore the power of words in sentences. Specifically, the framework employs the pre-trained full CLIP model as a dual encoder for the images and texts , taking advantage of prior cross-modal alignment knowledge. The Text-guided Image Restoration auxiliary task is proposed with the aim of implicitly mapping abstract textual entities to specific image regions, facilitating alignment between textual and visual embeddings. Additionally, we introduce a cross-modal triplet loss tailored for handling hard samples, enhancing the model's ability to distinguish minor differences. To focus the model on the key components within sentences, we propose a novel text data augmentation technique. Our proposed methods achieve state-of-the-art results on three popular benchmark datasets, and the source code will be made publicly available shortly

Giant negative magnetoresistance induced by the chiral anomaly in individual Cd3As2 nanowires

Cd3As2 is a newly booming Dirac semimetal with linear dispersion along all three momentum directions and can be viewed as 3D analog of graphene. As breaking of either time reversal symmetry or spatial inversion symmetry, the Dirac semimetal is believed to transform into Weyl semimetal with exotic chiral anomaly effect, while the experimental evidence of the chiral anomaly is still missing in Cd3As2. Here we report the magneto-transport properties of individual Cd3As2 nanowires. Large negative magnetoresistance (MR) with magnitude of -63% at 60 K and -11% at 300 K are observed when the magnetic field is parallel with the electric field direction, giving the evidence of the chiral magnetic effect in Cd3As2 nanowires. In addition, the critical magnetic field BC, where there is an extremum of the negative MR, increases with increasing temperature. As the first observation of chiral anomaly induced negative MR in Cd3As2 nanowires, it may offer valuable insights for low dimensional physics in Dirac semimetals.Comment: 4 figure

EFFECTS OF GRAPE POMACE ON METABOLIC SYNDROME: DIABETES AND OBESITY

ABSTRACT Title of Document: EFFECTS OF GRAPE POMACE ON METABOLIC SYNDROME: DIABETES AND OBESITY Haiwen Li, Doctor of Philosophy, 2015 Directed by: Professor Thomas W. Castonguay Department of Nutrition and Food Science Diabetes and obesity are twin epidemics that are closely linked to each other. In the United States, diabetes currently affects approximately 29.1 million adults and children. The estimated economic cost of treating diabetic patients and their related complications reached $245 billion in the US in 2012. Additionally, the prevalence of obesity is increasing during the recent decades. The National Health and Nutrition Examination Survey 2011-2012 reported that more than two-thirds of US adults (68.5%) are overweight, and more than one-third (34.9%) were obese. Both diabetes and obesity are currently considered diseases. Although they cannot be completely cured, diabetes and obesity can sometimes be prevented by increasing physical activity and eating healthy foods. Producing healthy foods or healthy agro-produced supplements would be the first line of defense against such diseases. In search of plant products that can be used for preventative medicine, we recently discovered that grape pomace, the by-product from the waste of the wine and juice industries, has great potential to prevent diabetes and obesity. The fundamental goal of this research is to elucidate the molecular mechanism(s) of the grape pomace extract’s (GPE) preventive functions on diabetes and obesity, and to provide scientific evidence to guide its use in developing functional foods for diabetes and obesity prevention. We hypothesize that GPE may prevent diabetes and obesity through altering the expression of genes on the signaling or metabolic pathways that lead to diabetes and obesity manifestation. This research project targeted on 4 specific objectives: 1) to characterize the action of GPE in reducing postprandial hyperglycemia through inhibition of alpha-glucosidase; 2) to understand the mode of molecular action of GPE in control of diabetes; 3) to understand the mode of molecular action of GPE in control of obesity; 4) to examine the effects of GPE on diabetes and obesity at genome wide. Throughout these research activities, we provided molecular evidence toward understanding the mode action of GPE in preventing diabetes and obesity. Such knowledge will provide guidance for future studies in developing GPE as an alternative therapeutic for the control of diabetes and obesity. Moreover this study may also lead to food industry applications in producing functional foods for diabetic and obese populations

Reconstruction of inhomogeneous media by an iteration algorithm with a learned projector

This paper is concerned with the inverse problem of reconstructing an inhomogeneous medium from the acoustic far-field data at a fixed frequency in two dimensions. This inverse problem is severely ill-posed (and also strongly nonlinear), and certain regularization strategy is thus needed. However, it is difficult to select an appropriate regularization strategy which should enforce some a priori information of the unknown scatterer. To address this issue, we plan to use a deep learning approach to learn some a priori information of the unknown scatterer from certain ground truth data, which is then combined with a traditional iteration method to solve the inverse problem. Specifically, we propose a deep learning-based iterative reconstruction algorithm for the inverse problem, based on a repeated application of a deep neural network and the iteratively regularized Gauss-Newton method (IRGNM). Our deep neural network (called the learned projector in this paper) mainly focuses on learning the a priori information of the shape of the unknown contrast with a normalization technique in the training process and is trained to act like a projector which is helpful for projecting the solution into some feasible region. Extensive numerical experiments show that our reconstruction algorithm provides good reconstruction results even for the high contrast case and has a satisfactory generalization ability

Scanning tunneling microscopy and spectroscopy of nanoscale twisted bilayer graphene

Nanoscale twisted bilayer graphene (TBG) is quite instable and will change its structure to Bernal (or AB-stacking) bilayer with a much lower energy. Therefore, the lack of nanoscale TBG makes its electronic properties not accessible in experiment up to now. In this work, a special confined TBG is obtained in the overlaid area of two continuous misoriented graphene sheets. The width of the confined region of the TBG changes gradually from about 22 nm to 0 nm. By using scanning tunnelling microscopy, we studied carefully the structure and the electronic properties of the nanoscale TBG. Our results indicate that the low-energy electronic properties, including twist-induced van Hove singularities (VHSs) and spatial modulation of local density-of-state, are strongly affected by the translational symmetry breaking of the nanoscale TBG. Whereas, the electronic properties above the energy of the VHSs are almost not influenced by the quantum confinement even when the width of the TBG is reduced to only a single moire spot.Comment: 4 Figure