Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

Industry recommender systems usually suffer from highly-skewed long-tail item distributions where a small fraction of the items receives most of the user feedback. This skew hurts recommender quality especially for the item slices without much user feedback. While there have been many research advances made in academia, deploying these methods in production is very difficult and very few improvements have been made in industry. One challenge is that these methods often hurt overall performance; additionally, they could be complex and expensive to train and serve. In this work, we aim to improve tail item recommendations while maintaining the overall performance with less training and serving cost. We first find that the predictions of user preferences are biased under long-tail distributions. The bias comes from the differences between training and serving data in two perspectives: 1) the item distributions, and 2) user's preference given an item. Most existing methods mainly attempt to reduce the bias from the item distribution perspective, ignoring the discrepancy from user preference given an item. This leads to a severe forgetting issue and results in sub-optimal performance. To address the problem, we design a novel Cross Decoupling Network (CDN) (i) decouples the learning process of memorization and generalization on the item side through a mixture-of-expert architecture; (ii) decouples the user samples from different distributions through a regularized bilateral branch network. Finally, a new adapter is introduced to aggregate the decoupled vectors, and softly shift the training attention to tail items. Extensive experimental results show that CDN significantly outperforms state-of-the-art approaches on benchmark datasets. We also demonstrate its effectiveness by a case study of CDN in a large-scale recommendation system at Google.Comment: Accepted by KDD 2023 Applied Data Science (ADS) trac

Chronic kidney disease with malignant peripheral nerve sheath tumor of the ureter: a case report

Malignant peripheral nerve sheath tumors (MPNSTs) are a complex group of malignant tumors originating from nerve cells or benign peripheral nerve sheath tumors and are commonly found in major plexus/nerve root sites such as the limbs, head, and neck. Malignant peripheral nerve sheath tumors originating in the ureter are extremely rare. Herein, we report the case of a 63-year-old patient with a malignant peripheral nerve sheath tumor of the right ureter who underwent laparoscopic radical resection of the right kidney and ureter. The patient also had stage 5 chronic kidney disease (CKD). Therefore, chemotherapy and radiotherapy were not considered. No tumor recurrence was observed during the follow-up period

Online Streaming Video Super-Resolution with Convolutional Look-Up Table

Online video streaming has fundamental limitations on the transmission bandwidth and computational capacity and super-resolution is a promising potential solution. However, applying existing video super-resolution methods to online streaming is non-trivial. Existing video codecs and streaming protocols (\eg, WebRTC) dynamically change the video quality both spatially and temporally, which leads to diverse and dynamic degradations. Furthermore, online streaming has a strict requirement for latency that most existing methods are less applicable. As a result, this paper focuses on the rarely exploited problem setting of online streaming video super resolution. To facilitate the research on this problem, a new benchmark dataset named LDV-WebRTC is constructed based on a real-world online streaming system. Leveraging the new benchmark dataset, we proposed a novel method specifically for online video streaming, which contains a convolution and Look-Up Table (LUT) hybrid model to achieve better performance-latency trade-off. To tackle the changing degradations, we propose a mixture-of-expert-LUT module, where a set of LUT specialized in different degradations are built and adaptively combined to handle different degradations. Experiments show our method achieves 720P video SR around 100 FPS, while significantly outperforms existing LUT-based methods and offers competitive performance compared to efficient CNN-based methods

Attentive Mask CLIP

Image token removal is an efficient augmentation strategy for reducing the cost of computing image features. However, this efficient augmentation strategy has been found to adversely affect the accuracy of CLIP-based training. We hypothesize that removing a large portion of image tokens may improperly discard the semantic content associated with a given text description, thus constituting an incorrect pairing target in CLIP training. To address this issue, we propose an attentive token removal approach for CLIP training, which retains tokens with a high semantic correlation to the text description. The correlation scores are computed in an online fashion using the EMA version of the visual encoder. Our experiments show that the proposed attentive masking approach performs better than the previous method of random token removal for CLIP training. The approach also makes it efficient to apply multiple augmentation views to the image, as well as introducing instance contrastive learning tasks between these views into the CLIP framework. Compared to other CLIP improvements that combine different pre-training targets such as SLIP and MaskCLIP, our method is not only more effective, but also much more efficient. Specifically, using ViT-B and YFCC-15M dataset, our approach achieves $43.9\%$ top-1 accuracy on ImageNet-1K zero-shot classification, as well as $62.7/42.1$ and $38.0/23.2$ I2T/T2I retrieval accuracy on Flickr30K and MS COCO, which are $+1.1\%$, $+5.5/+0.9$, and $+4.4/+1.3$ higher than the SLIP method, while being $2.30\times$ faster. An efficient version of our approach running $1.16\times$ faster than the plain CLIP model achieves significant gains of $+5.3\%$, $+11.3/+8.0$, and $+9.5/+4.9$ on these benchmarks

Association of Dopamine D2 Receptor Gene Polymorphisms with Reproduction Traits in Domestic Pigeons (Columba livia)

Dopamine inhibited prolactin secretion via dopamine D2 receptor (DRD2) at the pituitary level, but its effects on reproduction in pigeons are unclear. In this study, Single Nucleotide Polymorphisms (SNPs) in the exons of DRD2 gene were identified and analyzed by using DNA sequencing methods in 60 female domestic pigeons (Columba livia), and the association between DRD2 polymorphisms and reproduction traits was also analyzed. Sequencing results showed that 7 nucleotide mutations were detected in the exon 1, 4, and 6 regions of DRD2 gene. The analysis revealed three genotypes (AA, AB, and BB) in exon 4 and two genotypes (AA, AB) in exon 6, in which the AA genotype was consistently dominant, and the A allele showed a dominant advantage. The C4532T genotypes located in exon 6 of DRD2 gene were significantly (P<0.05) associated with reproductive traits of pigeon. Moreover, the individuals with AB genotype had significantly higher fertility rate and total hatching number within 500 days of age than those with AA genotype (P<0.05). These findings suggested that the DRD2 gene should be included in future genetic studies of pigeon reproduction and the SNP of C4532T might be a potential candidate genetic marker for Marker-aid breeding in pigeon

Engineering application architecture study on an LCC parallel MTDC transmission system

Multi-terminal DC (MTDC) transmission system is one of the effective technical means to perform a wide range connection of energy and load centres, also it has strong competitiveness and is economic efficiency. This study proposes full-scale studies on engineering application architecture of an MTDC system. Firstly, advantages and weaknesses of several typical types of MTDC are analysed, and based on the LCC parallel MTDC (P-MTDC) system, which is most applicable among all types, detailed studies are done on main topology, including polarity-reversal switches to realise power reversion; secondly, P-MTDC main circuit calculation method is presented, which decoupled the main circuit calculation into two parts: DC network and converter equation calculation, and general admittance matrix of the DC network is deduced in the study; thirdly, a novel constant-U control strategy is proposed to simplify the control logic and reduce the control system complexity, by means of setting the nearest point of common coupling from the rectifier station as the voltage control reference point. Finally, one practical case study is taken, for example, of a certain three-terminal DC project in the world, rated DC parameters are calculated, and a simulation model of MTDC system is built on Electro Magnetic Transient in DC System (EMTDC). The validity of the polarity-reversal control strategy proposed in the study is demonstrated by simulation

Expression Analysis of the PITX2 Gene and Associations between Its Polymorphisms and Body Size and Carcass Traits in Chickens

PITX2 is expressed in and plays an important role in myocytes of mice, and it has effects on late myogenic differentiation in chickens. However, the expression profile and polymorphisms of PITX2 remain unclear in chickens. Therefore, the aim of the present study was to detect its expression and investigate single nucleotide polymorphisms (SNPs) within its exons and then to evaluate whether these polymorphisms affect body size as well as carcass traits in chickens. The expression analysis showed that the expression level of chicken PITX2 mRNA in the leg muscle and hypophysis was significantly higher (p < 0.01) than those in other tissues. The results of polymorphisms analysis identified two SNPs (i.e., g.9830C > T and g.10073C > T) in exon 1 and 10 SNPs (i.e., g.12713C > T, g.12755C > T, g.12938G > A, g. 3164C > T, g.13019G > A, g.13079G > A, g.13285G > A, g.13335G > A, g.13726A > G and g.13856C > T) in exon 3, including four novel SNPs (i.e., g.9830C > T, g.12713C > T, g.12938G > A and g.13856C > T). In the loci of g.10073C > T and g.12713C > T, chickens with the CT genotype had the highest (p < 0.05 or p < 0.01) breast depth and breast angle, respectively. For the locus of g.13335G > A, chickens with the GG genotype had the highest (p < 0.05 or p < 0.01) breast angle and shank circumference. For the locus of g.13726A > G, chickens with the GG genotype had the highest breast width, fossil keel bone length and shank circumference. The locus of g.12713A > G had significant effects on the PITX2 mRNA expression level in leg muscle. The H1H7 diplotype showed the highest shank circumference, and the H2H8 diplotype showed the highest breast muscle rate. The present research suggested that polymorphisms of the exons of the PITX2 gene were significantly associated with the body size and carcass traits of Wuliang Mountain Black-bone chickens and the PITX2 gene could be a potential candidate gene for molecular marker-aided selection in Wuliang Mountain Black-bone chickens and other chicken breeds

Association of MyoD1 Gene Polymorphisms with Meat Quality Traits in Domestic Pigeons (Columba livia)

Myogenic differentiation 1 (MyoD1) belongs to the MyoD family and plays a key role in myogenesis and consequently, in determining muscle fiber characteristics. In this study, single nucleotide polymorphisms (SNPs) in the exons of MyoD1 were identified in 200 domestic pigeons (Columba livia) by direct DNA sequencing, and the association between MyoD1 polymorphisms and meat quality traits was analyzed. We found four novel variations (A2967G, G3044A, A3164C, and C3311G) in exon 3. The SNP A2967G is a synonymous mutation, while the other 3 SNPs are located in the 3′ untranslated region. The analysis revealed 3 genotypes, in which allele A was the predominant allele in the SNP A2967G, while allele B was the predominant allele in the SNPs G3044A and A3164C. The mutations A2967G and G3044A were significantly associated with meat quality traits in pigeon. Pigeons with AA or AB genotypes had higher breast muscle concentrations of inosinic acid and intramuscular fat than those of BB genotype. Moreover, these 2 SNPs had significant effects on MyoD1 mRNA expression. The SNPs A2967G and G3044A were organized into 4 haplotypes, which formed 7 diplotypes. Association analysis showed that the diplotypes were not significantly associated with meat quality traits. Our results implied that associations do exist between MyoD1 gene polymorphisms and meat quality traits in domestic pigeons, and the AA and AB genotypes could be applied as genetic markers in marker-aid pigeon breeding