Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences

A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels. Hence the method suffers from a lack of detailed geometry. To resolve this issue, we propose Y^2Seq2Seq, a view-based model, to learn cross-modal representations by joint reconstruction and prediction of view and word sequences. Specifically, the network architecture of Y^2Seq2Seq bridges the semantic meaning embedded in the two modalities by two coupled `Y' like sequence-to-sequence (Seq2Seq) structures. In addition, our novel hierarchical constraints further increase the discriminability of the cross-modal representations by employing more detailed discriminative information. Experimental results on cross-modal retrieval and 3D shape captioning show that Y^2Seq2Seq outperforms the state-of-the-art methods.Comment: To be pubilished at AAAI 201

Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Large pre-trained models (LPMs), such as LLaMA and ViT-G, have shown exceptional performance across various tasks. Although parameter-efficient fine-tuning (PEFT) has emerged to cheaply fine-tune these large models on downstream tasks, their deployment is still hindered by the vast model scale and computational costs. Neural network pruning offers a solution for model compression by removing redundant parameters, but most existing methods rely on computing parameter gradients. However, obtaining the gradients is computationally prohibitive for LPMs, which necessitates the exploration of alternative approaches. To this end, we propose a unified framework for efficient fine-tuning and deployment of LPMs, termed LoRAPrune. We first design a PEFT-aware pruning criterion, which utilizes the values and gradients of Low-Rank Adaption (LoRA), rather than the gradients of pre-trained parameters for importance estimation. We then propose an iterative pruning procedure to remove redundant parameters while maximizing the advantages of PEFT. Thus, our LoRAPrune delivers an accurate, compact model for efficient inference in a highly cost-effective manner. Experimental results on various tasks demonstrate that our method achieves state-of-the-art results. For instance, in the VTAB-1k benchmark, LoRAPrune utilizes only 0.76% of the trainable parameters and outperforms magnitude and movement pruning methods by a significant margin, achieving a mean Top-1 accuracy that is 5.7% and 4.3% higher, respectively. Moreover, our approach achieves comparable performance to PEFT methods, highlighting its efficacy in delivering high-quality results while benefiting from the advantages of pruning

Properties of jet-plated Ni coating on Ti alloy (Ti6Al4V) with laser cleaning pretreatment

The surface mechanical properties of the Selective Laser Melting (SLM) formed Ti6Al4V samples were improved by adopting a novel laser cleaning pretreatment process combined with a jet electrodeposition process. This paper aimed to investigate the effects of different laser powers on the morphologies and adhesions of the nickel coatings. The advantages of the laser cleaning process are no grinding, no contact, high efficiency and environmental protection. The morphologies, adhesion, wear resistance, and hardness of the coatings were characterized. The results indicate that when the laser energy density reached 20% (4 J/cm2), the contaminations on the substrate and the oxide layer were removed and the crystalline grain of the coating was 15.3 nm. The shallow pits generated by laser burning increased the adhesion of the coatings. In addition, when the laser energy density increased to 6 J/cm2, a yellow oxide layer was produced on the surface of the cleaned titanium alloy. Moreover, the wear resistance of the titanium alloy after the nickel plating was improved. The wear volume was only 0.046 mm3, and the hardness increased to 1967.6 N/mm2

A rare case of 2D+1D → 2D Cd(II) coordination polymer without any entanglements: Synthesis, structure and luminescent property

The reactions of CdCl2·2.5H2O with mixed ligands, H2tfbdc and hmt, under different metal-to-ligand ratios, afford two coordination polymers, namely, [Cd(hmt)(tfbdc)(H2O)2]2·3H2O (1) and {[NH4]2[Cd2(H2hmt)(tfbdc)2Cl4][Cd(H2hmt) (tfbdc)Cl2]}·2H2O (2). Both the complexes have been structurally characterized by X-ray data. Complex 1 has a 2D rectangular grid built up by tfbdc2– and hmt ligands, while 2 consists of distinct 1D anionic ladder [Cd2(H2hmt)(tfbdc)2Cl4]2‒ and 2D grid [Cd(H2hmt)(tfbdc)Cl2] in a crystal. Further, in 2, the 2D net is parallel to the 1D ladder without mutual entanglement or interdigitation. Despite the hydrogen bond interactions and the F···F interactions, only a 2D supermolecular structure is formed in 2. Thus, compound 2 is the first case of 2D+1D→2D coordination polymer without any entanglements

Single Fasting Plasma Glucose Versus 75-g Oral Glucose-Tolerance Test in Prediction of Adverse Perinatal Outcomes::A Cohort Study

Background: There remains uncertainty regarding whether a single fasting glucose measurement is sufficient to predict risk of adverse perinatal outcomes. Methods: We included 12,594 pregnant women who underwent a 75-g oral glucose-tolerance test (OGTT) at 22–28 weeks' gestation in the Born in Guangzhou Cohort Study, China. Outcomes were large for gestational age (LGA) baby, cesarean section, and spontaneous preterm birth. We calculated the area under the receiver operator characteristic curves (AUCs) to assess the capacity of OGTT glucose values to predict adverse outcomes, and compared the AUCs of different components of OGTT. Results: 1325 women had a LGA baby (10.5%). Glucose measurements were linearly associated with LGA, with strongest associations for fasting glucose (odds ratio 1.37, 95% confidence interval 1.30–1.45). Weaker associations were observed for cesarean section and spontaneous preterm birth. Fasting glucose have a comparable discriminative power for prediction of LGA to the combination of fasting, 1 h, and 2 h glucose values during OGTT (AUCs, 0.611 vs. 0.614, P = 0.166). The LGA risk was consistently increased in women with abnormal fasting glucose (≥5.1 mmol/l), irrespective of 1 h or 2 h glucose levels. Conclusions: A single fasting glucose measurement performs comparably to 75-g OGTT in predicting risk of having a LGA baby

No genetic causal association between iron status and osteoporosis: A two-sample Mendelian randomization

ObjectiveTo explore the genetic causal association between osteoporosis (OP) and iron status through Mendelian randomization (MR).MethodsPublicly available genome-wide association study (GWAS) summary data were used for MR analysis with four iron status-related indicators (ferritin, iron, total iron binding capacity, and transferrin saturation) as exposures and three different types of OP (OP, OP with pathological fracture, and postmenopausal OP with pathological fracture) as outcomes. The inverse-variance weighted (IVW) method was used to analyze the genetic causal association between the four indicators of iron status and OP. The heterogeneity of MR results was determined using IVW and MR–Egger methods. The pleiotropy of MR results was determined using MR–Egger regression. A leave-one-SNP-out test was performed to determine whether the MR results were affected by a single nucleotide polymorphism (SNP). The weighted median method was conducted to further validate our results.ResultsBased on IVW, MR–Egger and weighted median models, we found no causal association between iron status (ferritin, iron, total iron binding capacity, or transferrin saturation) and OP (Pbeta > 0.05 in all models). IVW and MR–Egger analysis of OP with pathological fracture and iron status indicators showed no potential genetic causal association (Pbeta> 0.05 in the two analyses). The results of the weighted median were consistent with those of IVW (Pbeta> 0.05 in all analyses). There was no potential genetic causal association between iron status and postmenopausal OP with pathological fracture based on serum iron (Pbeta>0.05 in all models). No heterogeneity or horizontal pleiotropy was found in any of the analyses. None of the leave-one-out tests in the analyses found any SNP that could affect the results of MR.ConclusionOur results demonstrate that there is no genetic causal association between OP and iron status, but the effects of other factors were not excluded