A Social Network Analysis of Consumers’ Perceived Brand Positions in the Running Shoes Market

Despite the slightly downturn in the footwear market due to weak economic performance in the US, the sales of running shoes gains steadily to $2.46 billion in 2011(Running USA, 2012) . However, increased intensity of competition in this section leads to more homogeneous products. Products targeting the same needs or competing on the same attributes decrease the profitability of the market as well as of each player (Porter, 1979). Therefore, branding strategies aiming at establishing a unique brand position in the market is crucial for all the brands in the running shoes market

Exploring College Students’ Shopping Motivation for Secondhand Clothing

Trade and use of secondhand clothing has been a norm of the western society since antiquity. Today, popularity of vintage fashion, desire for uniqueness and conspicuously low prices of branded luxury used clothes has given rise to a range of consignment stores, boutiques, and high-street concessions that resell previously worn garments (Hansen 2010). Although trade of secondhand clothing is on increase, there is lack of research done on motives that drive consumers to purchase secondhand clothing

CRABR-Net: A Contextual Relational Attention-Based Recognition Network for Remote Sensing Scene Objective

Remote sensing scene objective recognition (RSSOR) plays a serious application value in both military and civilian fields. Convolutional neural networks (CNNs) have greatly enhanced the improvement of intelligent objective recognition technology for remote sensing scenes, but most of the methods using CNN for high-resolution RSSOR either use only the feature map of the last layer or directly fuse the feature maps from various layers in the summation way, which not only ignores the favorable relationship information between adjacent layers but also leads to redundancy and loss of feature map, which hinders the improvement of recognition accuracy. In this study, a contextual, relational attention-based recognition network (CRABR-Net) was presented, which extracts different convolutional feature maps from CNN, focuses important feature content by using a simple, parameter-free attention module (SimAM), fuses the adjacent feature maps by using the complementary relationship feature map calculation, improves the feature learning ability by using the enhanced relationship feature map calculation, and finally uses the concatenated feature maps from different layers for RSSOR. Experimental results show that CRABR-Net exploits the relationship between the different CNN layers to improve recognition performance, achieves better results compared to several state-of-the-art algorithms, and the average accuracy on AID, UC-Merced, and RSSCN7 can be up to 96.46%, 99.20%, and 95.43% with generic training ratios

Effects of the seedling tray overlapping for seed emergence mode on emergence characteristics and growth of rice seedlings

Seedling mode plays a crucial role in the rice production process, as it significantly affects the growth and development of seedlings. Among the various seedling modes, the seedling tray overlapping for seed emergence mode (STOSE mode) has been demonstrated to be effective in enhancing seedling quality. However, the impact of this mode on the germination and growth of seeds with varying plumpness remains uncertain. To investigate the effect of the STOSE mode on seedling emergence characteristics, growth uniformity, and nutrient uptake of seeds with varying plumpness levels, we conducted a study using super early rice Zhongzao 39 (ZZ39) as the test material. The seeds were categorized into three groups: plumped, mixed, and unplumped. The results indicated that the STOSE mode significantly improved the seedling rate for all types of seeds in comparison to the seedling tray nonoverlapping for seed emergence mode (TSR mode). Notably, the unplumped seeds exhibited the most pronounced enhancement effect. The soluble sugar content of the seeds increased significantly after 2 days of sowing under the STOSE mode, whereas the starch content exhibited a significant decrease. Furthermore, the STOSE mode outperformed the TSR mode in several aspects including seedling growth uniformity, aboveground dry matter mass, root traits, and nutrient uptake. Overall, the STOSE mode not only promoted the germination and growth of plumped and mixed seeds but also had a more pronounced impact on unplumped seeds

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodal understanding and generation. The InternVid dataset contains over 7 million videos lasting nearly 760K hours, yielding 234M video clips accompanied by detailed descriptions of total 4.1B words. Our core contribution is to develop a scalable approach to autonomously build a high-quality video-text dataset with large language models (LLM), thereby showcasing its efficacy in learning video-language representation at scale. Specifically, we utilize a multi-scale approach to generate video-related descriptions. Furthermore, we introduce ViCLIP, a video-text representation learning model based on ViT-L. Learned on InternVid via contrastive learning, this model demonstrates leading zero-shot action recognition and competitive video retrieval performance. Beyond basic video understanding tasks like recognition and retrieval, our dataset and model have broad applications. They are particularly beneficial for generating interleaved video-text data for learning a video-centric dialogue system, advancing video-to-text and text-to-video generation research. These proposed resources provide a tool for researchers and practitioners interested in multimodal video understanding and generation.Comment: Data and Code: https://github.com/OpenGVLab/InternVideo/tree/main/Data/InternVi

Health status of the population in Naqu, Tibet and its latent class analysis: a cross-sectional survey

BackgroundThrough a survey and analysis of the population’s present state of health, it is possible to give data support for improving the health status of inhabitants in Naqu, Tibet. Additionally, it is possible to provide specific recommendations for the development of medical and healthcare facilities in Tibet.MethodsThe health scores of the participants were based on their responses to the four main sections of the questionnaire: dietary habits, living habits, health knowledge, and clinical disease history, and the variability of health status among groups with different characteristics was analyzed based on the scores. The four major sections were used to create classes of participants using latent class analysis (LCA). Using logistic regression, the factors influencing the classification of latent classes of health status were investigated.ResultsA total of 995 residents from 10 counties in Naqu were selected as the study subjects. And their demographic characteristics were described. The mean health score of residents after standardization was 81.59 ± 4.68. With the exception of gender, health scores differed between groups by age, education level, different occupations, marital status, and monthly income. The health status in Naqu, Tibet, was divided into two groups (entropy = 0.29, BLRT = 0.001, LMRT = 0.001) defined as the “good health group” and the “general health group.” A monthly income of more than ¥5000 adverse to good health in Naqu, Tibet.DiscussionSingle, well-educated young adults in Naqu, Tibet, have outstanding health. The vast majority of people in Tibet’s Naqu region were in good health. Furthermore, the population’s latent health status was divided into two classes, each with good dietary and living habits choices, low health knowledge, and a history of several clinical diseases. Univariate and multivariate logistic regression analysis showed that monthly income more than ¥5000 was an independent risk factor for poor health status

Coordinated Silencing of MYC-Mediated miR-29 by HDAC3 and EZH2 as a Therapeutic Target of Histone Modification in Aggressive B-Cell Lymphomas

We investigated the transcriptional and epigenetic repression of miR-29 by MYC, HDAC3, and EZH2 in mantle cell lymphoma and other MYC-associated lymphomas. We demonstrate that miR-29 is repressed by MYC through a corepressor complex with HDAC3 and EZH2. MYC contributes to EZH2 upregulation via repression of the EZH2 targeting miR-26a, and EZH2 induces MYC via inhibition of the MYC targeting miR-494 to create positive feedback. Combined inhibition of HDAC3 and EZH2 cooperatively disrupted the MYC-EZH2-miR-29 axis, resulting in restoration of miR-29 expression, downregulation of miR-29-targeted genes, and lymphoma growth suppression in vitro and in vivo. These findings define a MYC-mediated miRNA repression mechanism, shed light on MYC lymphomagenesis mechanisms, and reveal promising therapeutic targets for aggressive B-cell malignancies

Expert Consensus on Microtransplant for Acute Myeloid Leukemia in Elderly Patients -Report From the International Microtransplant Interest Group

Recent studies have shown that microtransplant (MST) could improve outcome of patients with elderly acute myeloid leukemia (EAML). To further standardize the MST therapy and improve outcomes in EAML patients, based on analysis of the literature on MST, especially MST with EAML from January 1st, 2011 to November 30th, 2022, the International Microtransplant Interest Group provides recommendations and considerations for MST in the treatment of EAML. Four major issues related to MST for treating EAML were addressed: therapeutic principle of MST (1), candidates for MST (2), induction chemotherapy regimens (3), and post-remission therapy based on MST (4). Others included donor screening, infusion of donor cells, laboratory examinations, and complications of treatment

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely