Influence of aluminium sheet surface modification on the self-piercing riveting process and the joint static lap shear strength

Self-piercing riveting (SPR) has been widely used in automotive as one of the major joining technologies for aluminium structures due to its advantages over some of the more traditional joining technologies. Research has shown that friction is a very important factor that influences both the riveting process and the joint strength for SPR, but these influences have not been fully understood. In this paper, AA5754 sheets with different surface textures, such as original with solid wax, hot water washed, sandpaper ground and grit blasted, were used to study the influence of friction on therivet inserting process, joint features and static lap shear strength. The results of joint features and rivet setting displacement-force curve showed that hot water wash and sandpaper grinding on aluminium sheet did not have significant influence on the rivet inserting process and joint features; however, for joints with grit-blasted substrates, the rivet -setting forces were higher at the beginning, and a middle section of the curve and the joint features, such as interlocks and minimum remaining bottom material thickness (Tmin), were clearly altered. The lap shear tests showed that hot water washing can slightly increase the lap shear strength, sandpaper grinding increased the static lap shear strength further and grit blasting increased the static lap shear strength the most

The Association between Virus Prevalence and Intercolonial Aggression Levels in the Yellow Crazy Ant, Anoplolepis Gracilipes (Jerdon).

The recent discovery of multiple viruses in ants, along with the widespread infection of their hosts across geographic ranges, provides an excellent opportunity to test whether viral prevalence in the field is associated with the complexity of social interactions in the ant population. In this study, we examined whether the association exists between the field prevalence of a virus and the intercolonial aggression of its ant host, using the yellow crazy ant (Anoplolepis gracilipes) and its natural viral pathogen (TR44839 virus) as a model system. We delimitated the colony boundary and composition of A. gracilipes in a total of 12 study sites in Japan (Okinawa), Taiwan, and Malaysia (Penang), through intercolonial aggression assay. The spatial distribution and prevalence level of the virus was then mapped for each site. The virus occurred at a high prevalence in the surveyed colonies of Okinawa and Taiwan (100% infection rate across all sites), whereas virus prevalence was variable (30%-100%) or none (0%) at the sites in Penang. Coincidentally, colonies in Okinawa and Taiwan displayed a weak intercolonial boundary, as aggression between colonies is generally low or moderate. Contrastingly, sites in Penang were found to harbor a high proportion of mutually aggressive colonies, a pattern potentially indicative of complex colony composition. Our statistical analyses further confirmed the observed correlation, implying that intercolonial interactions likely contribute as one of the effective facilitators of/barriers to virus prevalence in the field population of this ant species

CHAPTER: Exploiting Convolutional Neural Network Adapters for Self-supervised Speech Models

Self-supervised learning (SSL) is a powerful technique for learning representations from unlabeled data. Transformer based models such as HuBERT, which consist a feature extractor and transformer layers, are leading the field in the speech domain. SSL models are fine-tuned on a wide range of downstream tasks, which involves re-training the majority of the model for each task. Previous studies have introduced applying adapters, which are small lightweight modules commonly used in Natural Language Processing (NLP) to adapt pre-trained models to new tasks. However, such efficient tuning techniques only provide adaptation at the transformer layer, but failed to perform adaptation at the feature extractor. In this paper, we propose CHAPTER, an efficient tuning method specifically designed for SSL speech model, by applying CNN adapters at the feature extractor. Using this method, we can only fine-tune fewer than 5% of parameters per task compared to fully fine-tuning and achieve better and more stable performance. We empirically found that adding CNN adapters to the feature extractor can help the adaptation on emotion and speaker tasks. For instance, the accuracy of SID is improved from 87.71 to 91.56, and the accuracy of ER is improved by 5%.Comment: Submitted to ICASSP 2023. Under revie

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks

Transformer-based pre-trained models with millions of parameters require large storage. Recent approaches tackle this shortcoming by training adapters, but these approaches still require a relatively large number of parameters. In this study, AdapterBias, a surprisingly simple yet effective adapter architecture, is proposed. AdapterBias adds a token-dependent shift to the hidden output of transformer layers to adapt to downstream tasks with only a vector and a linear layer. Extensive experiments are conducted to demonstrate the effectiveness of AdapterBias. The experiments show that our proposed method can dramatically reduce the trainable parameters compared to the previous works with a minimal decrease in task performances compared with fine-tuned pre-trained models. We further find that AdapterBias automatically learns to assign more significant representation shifts to the tokens related to the task in consideration.Comment: The first two authors contributed equally. This paper was published in Findings of NAACL 202

Intra-articular injections of sodium hyaluronate (Hyalgan®) in osteoarthritis of the knee. a randomized, controlled, double-blind, multicenter trial in the asian population

<p>Abstract</p> <p>Background</p> <p>The efficacy and tolerability of 500-730 kDa sodium hyaluronate (Hyalgan^®) for treatment of osteoarthritis (OA) pain has been established in clinical trials, but few data are available in the Asian population. We conducted a randomized, double-blind, multicenter, placebo-controlled study to evaluate the efficacy and tolerability of this preparation in a Taiwanese population.</p> <p>Methods</p> <p>Two hundred patients with mild to moderate OA of the knee were randomized to receive five weekly intra-articular injections of sodium hyaluronate or placebo. The primary efficacy outcome was the change from baseline to Week 25 in patients' evaluation of pain using a 100-mm visual analog scale (VAS) during the 50-foot walking test. Additional outcomes included Western Ontario and McMaster Universities (WOMAC) scores, time on the 50-foot walking test, patient's and investigator's subjective assessment of effectiveness, acetaminophen consumption, and the amounts of synovial fluid.</p> <p>Results</p> <p>The Hyalgan^®treatment group showed a significantly greater improvement from baseline to Week 25 in VAS pain on the 50-foot walking test than the placebo group (p = 0.0020). The Hyalgan^®group revealed significant improvements from baseline to week 25 in WOMAC pain and function score than the placebo group (p = 0.005 and 0.0038, respectively) Other outcomes, such as time on the 50-foot walking test and subjective assessment of effectiveness, did not show any significant difference between groups. Both groups were safe and well tolerated.</p> <p>Conclusions</p> <p>The present study suggests that five weekly intra-articular injections of sodium hyaluronate are well tolerated, can provide sustained relief of pain, and can improve function in Asian patients with osteoarthritis of the knee.</p> <p>Level of Evidence</p> <p>Therapeutic study, Level I-1a (randomized controlled trial with a significant difference).</p> <p>Trial registration</p> <p>ClinicalTrials.gov Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01319461">NCT01319461</a></p