THE INFLUENCE OF PRODUCT PRESENTATION MODE AND ACADEMIC MAJOR ON THE MOTIVATION OF HAPTIC

Purpose of the study: This study was aimed to investigate the effect of product presentation mode and education background of the subject on the willingness of touch, preferences and visual imagery. Methodology: A total of 60 students were recruited to participate. The independent variables included product presentation mode (physical products, backgrounds removed image, scenario photo) and academic major of the subject (design major or management major). Three different kind dependent variables were measured in the study. On physical product condition, one sample was placed in front of subjects at a time. Both backgrounds removed image and scenario photo conditions, the subjects view experimental photos through a 22-inch LCD screen. They watched the sample item for 10 seconds and then were asked to assess the subjective questionnaire. Main Findings: The study results showed that when watching a physical product, the motivation of touch was greatest. The scenario photo generated more positive feelings and resulted in higher preference rating. The willingness of touch, preference and sensory ratings of management major students were higher than design major students. Applications of this study: The findings of this study can serve as a reference for enterprises to properly present products on web pages in order to increase consumers’ motivation to touch and preference. Novelty/Originality of this study: This study reinforces construction of a model of motivation to touch, and find that product presentation mode significant affect motivation to touch, preference and novelty feeling

Phase diagram and thermal properties of strong-interaction matter

We introduce a novel procedure for computing the (mu,T)-dependent pressure in continuum QCD; and therefrom obtain a complex phase diagram and predictions for thermal properties of the system, providing the in-medium behaviour of the trace anomaly, speed of sound, latent heat and heat capacity.Comment: 6 pages, 4 figures. Minor amendments in the version accepted for publicatio

Kerr-Sen Black Hole as Accelerator for Spinning Particles

It has been proved that arbitrarily high-energy collision between two particles can occur near the horizon of an extremal Kerr black hole as long as the energy $E$ and angular momentum $L$ of one particle satisfies a critical relation, which is called the BSW mechanism. Previous researchers mainly concentrate on geodesic motion of particles. In this paper, we will take spinning particle which won't move along a timelike geodesic into our consideration, hence, another parameter $s$ describing the particle's spin angular momentum was introduced. By employing the Mathisson-Papapetrou-Dixon equation describing the movement of spinning particle, we will explore whether a Kerr-Sen black hole which is slightly different from Kerr black hole can be used to accelerate a spinning particle to arbitrarily high energy. We found that when one of the two colliding particles satisfies a critical relation between the energy $E$ and the total angular momentum $J$, or has a critical spinning angular momentum $s_c$, a divergence of the center-of-mass energy $E_{cm}$ will be obtained.Comment: Latex,17 pages,1 figure,minor revision,accepted by PR

Nutritional profiles of tiger Nut (Cyperus esculentus) plant organs during its growth cycle

This study was carried out to determine major nutrient profiles changes of tiger nut plant during its growth period. The plant leaves, roots, tuber moisture, starch, fat and protein were analyzed by oven drying, enzymatic hydrolysis, glucose assay, soxhlet extraction and kjeldahl methods. The results show the moisture content was decreased during its growth cycle but varied with different plant organ. For leaves, the starch content was increased with reducing oil content. For roots, oil content was highest (8%) at the 100th day, and it was gradually decreased (3%) till harvest time with non-significant changes of starch content. For tuber, reducing sugar and protein content was insignificant where the starch and oil content increased significantly but the changes were irregular in the middle growing. For optimum macronutrient yields, it is recommended to harvest the plant at 142nd day for starch. The delayed harvesting may lead to increase in oil content while reducing its total starch contents. For the starch purpose, the harvest time could be around 142 days. However, harvest time could require staying longer in soil.Keywords: Tiger nut, oil, starch, growth cycle, nutrients enrichmen

In-context Autoencoder for Context Compression in a Large Language Model

We propose the In-context Autoencoder (ICAE) for context compression in a large language model (LLM). The ICAE has two modules: a learnable encoder adapted with LoRA from an LLM for compressing a long context into a limited number of memory slots, and a fixed decoder which is the target LLM that can condition on the memory slots for various purposes. We first pretrain the ICAE using both autoencoding and language modeling objectives on massive text data, enabling it to generate memory slots that accurately and comprehensively represent the original context. Then, we fine-tune the pretrained ICAE on a small amount of instruct data to enhance its interaction with various prompts for producing desirable responses. Our experimental results demonstrate that the ICAE learned with our proposed pretraining and fine-tuning paradigm can effectively produce memory slots with $4\times$ context compression, which can be well conditioned on by the target LLM to respond to various prompts. The promising results demonstrate significant implications of the ICAE for its novel approach to the long context problem and its potential to reduce computation and memory overheads for LLM inference in practice, suggesting further research effort in context management for an LLM. Our code and data will be released shortly.Comment: Work in progres

How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions

We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting MQR dataset is constructed from human contributed Stack Exchange question edit histories. The dataset contains 427,719 question pairs which come from 303 domains. We provide human annotations for a subset of the dataset as a quality estimate. When moving from ill-formed to well-formed questions, the question quality improves by an average of 45 points across three aspects. We train sequence-to-sequence neural models on the constructed dataset and obtain an improvement of 13.2% in BLEU-4 over baseline methods built from other data resources. We release the MQR dataset to encourage research on the problem of question rewriting.Comment: AAAI 202

The Regenerating Gene Iα Is Overexpressed in Atrophic Gastritis Rats with Hypergastrinemia

The role of gastrin on the development of atrophic gastritis (AG) and its relationship with the expression of RegIα  in vivo remain unclear. We established experimental AG in rats by combination administration with sodium salicylate, alcohol, and deoxycholate sodium. The mean score of inflammation in gastric antrum in AG rats was significantly elevated (P < 0.05), while the number of glands dramatically decreased (P < 0.05). In addition, the cell proliferation in gastric glands was increased in experimental AG rats, as determined by immunohistochemistry staining of PCNA and GS II. The level of serum gastrin in AG rats was significantly elevated relative to that of normal rats (P < 0.01). Moreover, the expression of RegIα protein and its receptor mRNA was increased in gastric tissues in AG rats (P < 0.05). Taken together, we demonstrated that the overexpression of Reglα is related with hypergastrinemia in AG rats

Visual-Textual Attribute Learning for Class-Incremental Facial Expression Recognition

In this paper, we study facial expression recognition (FER) in the class-incremental learning (CIL) setting, which defines the classification of well-studied and easily-accessible basic expressions as an initial task while learning new compound expressions gradually. Motivated by the fact that compound expressions are meaningful combinations of basic expressions, we treat basic expressions as attributes (i.e., semantic descriptors), and thus compound expressions are represented in terms of attributes. To this end, we propose a novel visual-textual attribute learning network (VTA-Net), mainly consisting of a textual-guided visual module (TVM) and a textual compositional module (TCM), for class-incremental FER. Specifically, TVM extracts textual-aware visual features and classifies expressions by incorporating the textual information into visual attribute learning. Meanwhile, TCM generates visual-aware textual features and predicts expressions by exploiting the dependency between textual attributes and category names of old and new expressions based on a textual compositional graph. In particular, a visual-textual distillation loss is introduced to calibrate TVM and TCM during incremental learning. Finally, the outputs from TVM and TCM are fused to make a final prediction. On the one hand, at each incremental task, the representations of visual attributes are enhanced since visual attributes are shared across old and new expressions. This increases the stability of our method. On the other hand, the textual modality, which involves rich prior knowledge of the relevance between expressions, facilitates our model to identify subtle visual distinctions between compound expressions, improving the plasticity of our method. Experimental results on both in-the-lab and in-the-wild facial expression databases show the superiority of our method against several state-of-the-art methods for class-incremental FER

Weak cosmic censorship conjecture for the novel 4D4D charged Einstein-Gauss-Bonnet black hole with test scalar field and particle

Recent researches of the novel $4D$ Einstein-Gauss-Bonnet (EGB) gravity have attracted great attention. In this paper, we investigate the validity of the weak cosmic censorship conjecture for a novel $4D$ charged EGB black hole with test charged scalar field and test charged particle respectively. For the test charged field scattering process, we find that both extremal and near-extremal black holes cannot be overcharged. For the test charged particle injection, to first order, an extremal black hole cannot be overcharged while a near-extremal $4D$ charged EGB black hole can be destroyed. To second order, however, both extremal and near-extremal $4D$ charged EGB black holes can be overcharged for positive Gauss-Bonnet coupling constant; for negative Gauss-Bonnet coupling constant, an extremal black hole cannot be overcharged and the validity of the weak cosmic censorship conjecture for a near-extremal black hole depends on the Gauss-Bonnet coupling constant.Comment: 13 pages,1 figure;V2: discussions and references added; V3: published versio