Processing and Characterization of Basalt Fiber Reinforced Ceramic Composites for High Temperature Applications Using Polymer Precursors

The development of high temperature structural composite materials has been very limited due to the high cost of the materials and the processing needed. Ceramics can take much higher temperatures, but they are difficult to produce and form in bulk volumes. Polymer Derived Ceramics (PDCs) begin as a polymer matrix, allowing a shape to be formed and cured and then to be pyrolized in order to obtain a ceramic with the associated thermal and mechanical properties. The two PDCs used in this development are polysiloxane and polycarbosilane. Polysiloxanes contain a silicon oxycarbide backbone when pyrolized up to 1000 deg C. Polycarbosilane, an organosilicon polymer, contain a silicon-carbon backbone; around 1200 deg C, Beta-SiC begins to crystallize. The use of basalt in structural and high temperature applications has been under development for over 50 years, yet there has been little published research on the incorporation of basalt fibers as a reinforcement in composites. Basalt is a naturally occurring material found in volcanic rock. Continuous basalt fiber reinforced PDCs have been fabricated and tested for the applicability of this composite system as a high temperature structural composite material. Thermal and mechanical testing includes oxyacetylene torch testing and three point bend testing

A streamlined Approach to Multimodal Few-Shot Class Incremental Learning for Fine-Grained Datasets

Few-shot Class-Incremental Learning (FSCIL) poses the challenge of retaining prior knowledge while learning from limited new data streams, all without overfitting. The rise of Vision-Language models (VLMs) has unlocked numerous applications, leveraging their existing knowledge to fine-tune on custom data. However, training the whole model is computationally prohibitive, and VLMs while being versatile in general domains still struggle with fine-grained datasets crucial for many applications. We tackle these challenges with two proposed simple modules. The first, Session-Specific Prompts (SSP), enhances the separability of image-text embeddings across sessions. The second, Hyperbolic distance, compresses representations of image-text pairs within the same class while expanding those from different classes, leading to better representations. Experimental results demonstrate an average 10-point increase compared to baselines while requiring at least 8 times fewer trainable parameters. This improvement is further underscored on our three newly introduced fine-grained datasets

Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection

Open World Object Detection (OWOD) is a challenging and realistic task that extends beyond the scope of standard Object Detection task. It involves detecting both known and unknown objects while integrating learned knowledge for future tasks. However, the level of "unknownness" varies significantly depending on the context. For example, a tree is typically considered part of the background in a self-driving scene, but it may be significant in a household context. We argue that this contextual information should already be embedded within the known classes. In other words, there should be a semantic or latent structure relationship between the known and unknown items to be discovered. Motivated by this observation, we propose Hyp-OW, a method that learns and models hierarchical representation of known items through a SuperClass Regularizer. Leveraging this representation allows us to effectively detect unknown objects using a similarity distance-based relabeling module. Extensive experiments on benchmark datasets demonstrate the effectiveness of Hyp-OW, achieving improvement in both known and unknown detection (up to 6 percent). These findings are particularly pronounced in our newly designed benchmark, where a strong hierarchical structure exists between known and unknown objects. Our code can be found at https://github.com/boschresearch/Hyp-OWComment: Accepted at AAAI 2024 || keywords: Open World Object Detection, Hyperbolic Distance, Unknown Detection, Deformable Transformers, Hierarchical Representation Learnin

UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models

In this study, we investigate the task of data pre-selection, which aims to select instances for labeling from an unlabeled dataset through a single pass, thereby optimizing performance for undefined downstream tasks with a limited annotation budget. Previous approaches to data pre-selection relied solely on visual features extracted from foundation models, such as CLIP and BLIP-2, but largely ignored the powerfulness of text features. In this work, we argue that, with proper design, the joint feature space of both vision and text can yield a better representation for data pre-selection. To this end, we introduce UP-DP, a simple yet effective unsupervised prompt learning approach that adapts vision-language models, like BLIP-2, for data pre-selection. Specifically, with the BLIP-2 parameters frozen, we train text prompts to extract the joint features with improved representation, ensuring a diverse cluster structure that covers the entire dataset. We extensively compare our method with the state-of-the-art using seven benchmark datasets in different settings, achieving up to a performance gain of 20%. Interestingly, the prompts learned from one dataset demonstrate significant generalizability and can be applied directly to enhance the feature extraction of BLIP-2 from other datasets. To the best of our knowledge, UP-DP is the first work to incorporate unsupervised prompt learning in a vision-language model for data pre-selection

A Time-Domain Boundary Element Method for Wave Diffraction in a Two-Layer Fluid

A time-domain numerical model is established based on the higher-order boundary element method (HOBEM) to simulate wave diffraction problem in a two-layer fluid of finite depth. There are two possible incident wave modes (surface-wave mode and internal-wave mode) exist in the incident wave for a prescribed frequency in a two-layer fluid. For surface-wave mode, the hydrodynamic characters of fluid particles are similar to single-layer fluid. For the internal-wave mode, through the definition of a new function respected to velocity potentials of upper and lower fluid on the interface by using matching condition, a single set of linear equations is set up to compute the time histories of wave forces and wave profiles by using a fourth-order Runge-Kutta method. An artificial damping layer is adopted both on the free surface and interface to avoid the wave reflection. Examinations of the accuracy of this time-domain algorithm are carried out for a truncated cylinder and a rectangular barge, and the results demonstrate the effectiveness of this method

Identification, Characterization, and Effects of Xenopus laevis PNAS-4 Gene on Embryonic Development

Apoptosis plays an important role in embryonic development. PNAS-4 has been demonstrated to induce apoptosis in several cancer cells. In this study, we cloned Xenopus laevis PNAS-4 (xPNAS-4), which is homologous to the human PNAS-4 gene. Bioinformatics analysis for PNAS-4 indicated that xPNAS-4 shared 87.6% identity with human PNAS-4 and 85.5% with mouse PNAS-4. The phylogenetic tree of PNAS-4 protein was also summarized. An analysis of cellular localization using an EGFP-fused protein demonstrated that xPNAS-4 was localized in the perinuclear region of the cytoplasm. RT-PCR analysis revealed that xPNAS-4, as a maternally expressed gene, was present in all stages of early embryo development. Whole-mount in situ hybridization showed that xPNAS-4 was mainly expressed in ectoderm and mesoderm. Furthermore, microinjection of xPNAS-4 mRNA in vivo caused developmental defects manifesting as a small eye phenotype in the Xenopous embryos, and as a small eye or one-eye phenotype in developing zebrafish embryos. In addition, embryos microinjected with xPNAS-4 antisense morpholino oligonucleotides (MOs) exhibited a failure of head development and shortened axis

Expressions of COX-2 and VEGF-C in gastric cancer: correlations with lymphangiogenesis and prognostic implications

<p>Abstract</p> <p>Background</p> <p>Cyclooxygenase-2 (COX-2) has recently been considered to promote lymphangiogenesis by up-regulating vascular endothelial growth factor-C (VEGF-C) in breast and lung cancer. However, the impact of COX-2 on lymphangiogenesis of gastric cancer remains unclear. This study aims to test the expression of COX-2 and VEGF-C in human gastric cancer, and to analyze the correlation with lymphatic vessel density (LVD), clinicopathologic features and survival prognosis.</p> <p>Methods</p> <p>Using immunohistochemistry, COX-2, VEGF-C and level of LVD were analyzed in 56 R0-resected primary gastric adenocarcinomas, while paracancerous normal mucosal tissues were also collected as control from 25 concurrent patients. The relationships among COX-2 and VEGF-C expression, LVD, and clinicopathologic parameters were analyzed. The correlations of COX-2, VEGF-C and level of LVD with patient prognosis were also evaluated by univariate tests and multivariate Cox regression.</p> <p>Results</p> <p>The expression rates of COX-2 and VEGF-C were 69.64% and 55.36%, respectively, in gastric carcinoma. Peritumoral LVD was significantly higher than that in both normal and intratumoral tissue (<it>P </it>< 0.05). It was significantly correlated with lymph node metastasis and invasion depth (<it>P </it>= 0.003, <it>P </it>= 0.05). VEGF-C was significantly associated with peritumoral LVD (<it>r </it>= 0.308, <it>P </it>= 0.021). However, COX-2 was not correlated with VEGF-C (<it>r </it>= 0.110, <it>P </it>= 0.419) or LVD (<it>r </it>= 0.042, <it>P </it>= 0.758). Univariate analysis showed that survival time was impaired by higher COX-2 expression and higher peritumoral LVD. Multivariate survival analysis showed that age, COX-2 expression and peritumoral LVD were independent prognostic factors.</p> <p>Conclusions</p> <p>Although COX-2 expression was associated with survival time, it was not correlated with VEGF-C and peritumoral LVD. Our data did not show that overexpression of COX-2 promotes tumor lymphangiogenesis through an up-regulation of VEGF-C expression in gastric carcinoma. Age, COX-2 and peritumoral LVD were independent prognostic factors for human gastric carcinoma.</p

Cough Test during Tension-Free Vaginal Tape Procedure in Preventing Postoperative Urinary Retention

Objective. To discuss the practical value of the cough test during the tension-free vaginal tape (TVT) procedure. Methods. In the first group, 41 patients of female stress incontinence received TVT operations which were performed according to the Ulmsten’s method strictly, only that the stress of tape was adjusted in light of the cough test. In the second group, 44 patients of female stress incontinence received TVT operations in which the tape was put under the urethral tract without stress, not adjusted by cough test. Results. The cure rate was 38/41 (92.6%) in the cough test group and 41/44 (93.1%) in the noncough test group; detrusor pressure-uroflow study indicated that there were 11 cases in the obstruction zone in the cough test group while only 3 cases were in the obstruction zone in the noncough test group; 4 cases of urinary retention and 5 cases of voiding dysfunction were found in the cough test group, while difficulties of urination were not found in the non-cough test group. Conclusion. Adjusting the tape stress in accordance with the cough test during the TVT can increase the opportunity of urinary retention or difficulty of urination after operation. So there is no benefit of the cough test during tension-free vaginal tape procedure in preventing post-operative urinary retention