Computational Technologies for Fashion Recommendation: A Survey

Fashion recommendation is a key research field in computational fashion research and has attracted considerable interest in the computer vision, multimedia, and information retrieval communities in recent years. Due to the great demand for applications, various fashion recommendation tasks, such as personalized fashion product recommendation, complementary (mix-and-match) recommendation, and outfit recommendation, have been posed and explored in the literature. The continuing research attention and advances impel us to look back and in-depth into the field for a better understanding. In this paper, we comprehensively review recent research efforts on fashion recommendation from a technological perspective. We first introduce fashion recommendation at a macro level and analyse its characteristics and differences with general recommendation tasks. We then clearly categorize different fashion recommendation efforts into several sub-tasks and focus on each sub-task in terms of its problem formulation, research focus, state-of-the-art methods, and limitations. We also summarize the datasets proposed in the literature for use in fashion recommendation studies to give readers a brief illustration. Finally, we discuss several promising directions for future research in this field. Overall, this survey systematically reviews the development of fashion recommendation research. It also discusses the current limitations and gaps between academic research and the real needs of the fashion industry. In the process, we offer a deep insight into how the fashion industry could benefit from fashion recommendation technologies. the computational technologies of fashion recommendation

Solving Math Word Problems with Reexamination

Math word problem (MWP) solving aims to understand the descriptive math problem and calculate the result, for which previous efforts are mostly devoted to upgrade different technical modules. This paper brings a different perspective of \textit{reexamination process} during training by introducing a pseudo-dual task to enhance the MWP solving. We propose a pseudo-dual (PseDual) learning scheme to model such process, which is model-agnostic thus can be adapted to any existing MWP solvers. The pseudo-dual task is specifically defined as filling the numbers in the expression back into the original word problem with numbers masked. To facilitate the effective joint learning of the two tasks, we further design a scheduled fusion strategy for the number infilling task, which smoothly switches the input from the ground-truth math expressions to the predicted ones. Our pseudo-dual learning scheme has been tested and proven effective when being equipped in several representative MWP solvers through empirical studies. \textit{The codes and trained models are available at:} \url{https://github.com/steven640pixel/PsedualMWP}. \end{abstract}Comment: To be appeared at NeurIPS2023 Workshop on MATH-A

Non-Autoregressive Sentence Ordering

Existing sentence ordering approaches generally employ encoder-decoder frameworks with the pointer net to recover the coherence by recurrently predicting each sentence step-by-step. Such an autoregressive manner only leverages unilateral dependencies during decoding and cannot fully explore the semantic dependency between sentences for ordering. To overcome these limitations, in this paper, we propose a novel Non-Autoregressive Ordering Network, dubbed \textit{NAON}, which explores bilateral dependencies between sentences and predicts the sentence for each position in parallel. We claim that the non-autoregressive manner is not just applicable but also particularly suitable to the sentence ordering task because of two peculiar characteristics of the task: 1) each generation target is in deterministic length, and 2) the sentences and positions should match exclusively. Furthermore, to address the repetition issue of the naive non-autoregressive Transformer, we introduce an exclusive loss to constrain the exclusiveness between positions and sentences. To verify the effectiveness of the proposed model, we conduct extensive experiments on several common-used datasets and the experimental results show that our method outperforms all the autoregressive approaches and yields competitive performance compared with the state-of-the-arts. The codes are available at: \url{https://github.com/steven640pixel/nonautoregressive-sentence-ordering}.Comment: Accepted at Findings of EMNLP202

Effects of species-dominated patches on soil organic carbon and total nitrogen storage in a degraded grassland in China

Background Patchy vegetation is a very common phenomenon due to long-term overgrazing in degraded steppe grasslands, which results in substantial uncertainty associated with soil carbon (C) and nitrogen (N) dynamics because of changes in the amount of litter accumulation and nutrition input into soil. Methods We investigated soil C and N stocks beneath three types of monodominant species patches according to community dominance. Stipa krylovii patches, Artemisia frigida patches, and Potentilla acaulis patches represent better to worse vegetation conditions in a grassland in northern China. Results The results revealed that the soil C stock (0–40 cm) changed significantly, from 84.7 to 95.7 Mg ha−1, and that the soil organic carbon content (0–10 cm) and microbial biomass carbon (0–10 and 10–20 cm) varied remarkably among the different monodominant species communities (P < 0.05). However, soil total nitrogen and microbial biomass nitrogen showed no significant differences among different plant patches in the top 0–20 cm of topsoil. The soil C stocks under the P. acaulis and S. krylovii patches were greater than that under the A. frigida patch. Our study implies that accurate estimates of soil C and N storage in degenerated grassland require integrated analyses of the concurrent effects of differences in plant community composition

MicroRNA-181a Functions as an Oncogene in Gastric Cancer by Targeting Caprin-1

MicroRNA-181a (miRNA-181a) is a multifaceted miRNA implicated in various cellular processes, particularly in cell fate determination and cellular invasion. It is frequently expressed aberrantly in human tumors and shows opposing functions in different types of cancers. In this study, we found that miRNA-181a is overexpressed in Gastric cancer (GC) tissues. Clinical and pathological analyses revealed that the expression of miRNA-181a is correlated with tumor size, lymph node metastasis, distant metastasis, and TNM stage. Kaplan-Meier analysis indicated that overexpression of miRNA-181a is associated with poor overall survival of patients with GC. Moreover, miRNA-181a is overexpressed in GC cells, and downregulation of miRNA-181a induced cell apoptosis and suppressed the proliferation, invasion, and metastasis of GC cells both in vitro and in vivo. Target prediction and luciferase reporter assay showed that caprin-1 was a direct target of miRNA-181a. Downregulation of caprin-1 expression resulted in a converse change with miRNA-181a in GC. Spearman’s correlation test confirmed that the expression of miRNA-181a expression was inversely correlated with that of caprin-1 in GC cells. Furthermore, the expression of caprin-1 increased after downregulation of miRNA-181a in the GC cells. Caprin-1 siRNA can rescue the oncogenic effect of miRNA-181a on GC cell proliferation, apoptosis, migration, and invasion. These findings suggest that miRNA-181a directly inhibits caprin-1 and promotes GC development. miRNA-181a could be a target for anticancer drug development

Anti-inflammatory recombinant TSG-6 stabilizes the progression of focal retinal degeneration in a murine model

<p>Abstract</p> <p>Background</p> <p>Inflammatory responses are detected in the retina of patients with age-related macular degeneration and <it>Ccl2^-/-/Cx3cr1^-/-</it>mice on rd8 background,(<it>Ccl2^-/-/Cx3cr1^-/-</it>mice) a model that develops progressive age-related macular degeneration-like retinal lesions including focal photoreceptor degeneration, abnormal retinal pigment epithelium and A2E accumulation. Tumor necrosis factor-inducible gene 6 protein is an anti-inflammatory protein and has been shown to improve myocardial infarction outcome and chemically injured cornea in mice by suppressing inflammation. In this study, we evaluated the effect of an intravitreous injection of recombinant TSG-6 on the retinal lesions of <it>Ccl2^-/-/Cx3cr1^-/-</it>mice.</p> <p>Methods</p> <p>Recombinant TSG-6 (400 ng) was administered by intravitreous injection into the right eye of six-week-old C<it>cl2^-/-/Cx3cr1^-/-</it>mice. Their left eye was injected with phosphate-buffered saline as a control. Funduscopic pictures were taken before injection and sequentially once a month after injection. The mice were killed two months after injection and the ocular histology examined. Retinal A2E, a major component of lipofuscin, was measured by high performance liquid chromatography. The microarray of ocular mRNA of 92 immunological genes was performed. The genes showing differentiated expression in microarray were further compared between the injected right eye and the contralateral (control) eye by [real-time quantitative reverse transcription polymerase chain reaction] qRT-PCR.</p> <p>Results</p> <p>The continuous monitoring of the fundus for two months showed a slower progression or alleviation of retinal lesions in the treated right eyes as compared with the untreated left eyes. Among 23 pairs of eyes, the lesion levels improved in 78.3%, stayed the same in 8.7% and progressed in 13.0%. Histology confirmed the clinical observation. Even though there was no difference in the level of A2E between the treated and the untreated eyes, microarray analysis of 92 immune genes showed that <it>IL-17a </it>was substantially decreased after the treatment. Expression of <it>TNF-α </it>showed a similar pattern to <it>IL-17a</it>. The results were consistent in duplicated arrays and confirmed by qRT-PCR.</p> <p>Conclusions</p> <p>We concluded that intravitreous administration of recombinant TSG-6 might stabilize retinal lesions in <it>Ccl2^-/-/Cx3cr1^-/-</it>mice on rd8 background. Modulation of ocular immunological gene expressions, especially IL-17a, could be one of the mechanisms.</p