The analysis of tool wear mechanisms in the machining of pre-sintered zirconia dental crowns

The growth of Digital Dentistry has opened new potentials in the dental restoration sector where personalised restorations could be made in a much shorter time than before. Zirconia has been widely used due to its excellent wear properties and bio-compatibility. Zirconia is machined primarily in its pre-sintered state, using carbide tools. Even in its pre-sintered state, zirconia is abrasive and caused tool wear. Tool wear is affected by tool substrate used, cutting conditions used, machining method employed, etc. Tool substrates are such as tungsten carbide, steel, etc. Cutting conditions refer to speed, feed, depth of cut, etc. Machining methods refer to milling wet or dry. Understanding tool wear helps in better tool design. Tools that lasted longer would mean the end users i.e. dental technicians would have less unproductive downtime changing tools. Also, worn tool would produce broken restorations which is undesirable. With this in mind, the aim of this paper was to study tool wear by identifying the wear mechanism that occurred when carbide tools machined pre-sintered zirconia. Test was constructed using recommendations from ISO 8688:1989. Cutting conditions used were adapted from those used in desktop dental milling machines. Pre-defined stopping criterion was set and flank wear of tool was measured every 15 minutes using an optical microscope. When tools reached the stopping criterion, Scanning Electron Microscope (SEM) and Electron Backscatter Diffraction (EBSD) were used to analyse worn tool in details. Findings showed transgranular and intergranular fractures were the wear mechanisms on carbide tools when machining pre-sintered zirconia

Investigations of the scavenger receptor class A and complement receptor 3 - Two pattern recognition receptors

Ph.DDOCTOR OF PHILOSOPH

Exploring Baba and Nyonya culture via multiple image lenses : food travellers’ perspective / Jason M. S. Lam...[et al.]

This study applies a multidimensional approach in the context of Baba and Nyonya cuisine. A total of 209 international food tourists were surveyed in Malacca, Malaysia. The results derived from structural equation modelling empirically confirmed that the cognitive image dimensions of safety, uniqueness and family-oriented significantly and positively influenced both affective and conative images. However, the cognitive image dimension of variety only partially influenced affective image, but not a conative image, while the cognitive image of cooking methods did not show any significant effects on the affective nor conative image. Finally, affective image dimensions significantly and positively influenced the conative image. Relevant implications, limitations, and suggestions for future studies for Baba and Nyonya cuisine also discussed

Position Prediction as an Effective Pretraining Strategy

Transformers have gained increasing popularity in a wide range of applications, including Natural Language Processing (NLP), Computer Vision and Speech Recognition, because of their powerful representational capacity. However, harnessing this representational capacity effectively requires a large amount of data, strong regularization, or both, to mitigate overfitting. Recently, the power of the Transformer has been unlocked by self-supervised pretraining strategies based on masked autoencoders which rely on reconstructing masked inputs, directly, or contrastively from unmasked content. This pretraining strategy which has been used in BERT models in NLP, Wav2Vec models in Speech and, recently, in MAE models in Vision, forces the model to learn about relationships between the content in different parts of the input using autoencoding related objectives. In this paper, we propose a novel, but surprisingly simple alternative to content reconstruction~-- that of predicting locations from content, without providing positional information for it. Doing so requires the Transformer to understand the positional relationships between different parts of the input, from their content alone. This amounts to an efficient implementation where the pretext task is a classification problem among all possible positions for each input token. We experiment on both Vision and Speech benchmarks, where our approach brings improvements over strong supervised training baselines and is comparable to modern unsupervised/self-supervised pretraining methods. Our method also enables Transformers trained without position embeddings to outperform ones trained with full position information.Comment: Accepted to ICML 202

Organic over-the-horizon targeting for the 2025 surface fleet

Please note that this activity was not conducted in accordance with Federal, DOD, and Navy Human Research Protection RegulationsAdversarial advances in the proliferation of anti-access/area-denial (A2/AD) techniques requires an innovative approach to the design of a maritime system of systems capable of detecting, classifying, and engaging targets in support of organic over-the-horizon (OTH) tactical offensive operations in the 2025–2030 timeframe. Using a systems engineering approach, this study considers manned and unmanned systems in an effort to develop an organic OTH targeting capability for U.S. Navy surface force structures of the future. Key attributes of this study include overall system requirements, limitations, operating area considerations, and issues of interoperability and compatibility. Multiple alternative system architectures are considered and analyzed for feasibility. The candidate architectures include such systems as unmanned aerial vehicles (UAVs), as well as prepositioned undersea and low-observable surface sensor and communication networks. These unmanned systems are expected to operate with high levels of autonomy and should be designed to provide or enhance surface warfare OTH targeting capabilities using emerging extended-range surface-to-surface weapons. This report presents the progress and results of the SEA-21A capstone project with the recommendation that the U.S. Navy explore the use of modestly-sized, network-centric UAVs to enhance the U.S. Navy’s ability to conduct surface-based OTH tactical offensive operations by 2025.http://archive.org/details/organicovertheho1094545933Approved for public release; distribution is unlimited

Cancer-related ectopic expression of the bone-related transcription factor RUNX2 in non-osseous metastatic tumor cells is linked to cell proliferation and motility

10.1186/bcr2762Breast Cancer Research125-BCRR

Simplified R-Symmetry Breaking and Low-Scale Gauge Mediation

We argue that some of the difficulties in constructing realistic models of low-scale gauge mediation are artifacts of the narrow set of models that have been studied. In particular, much attention has been payed to the scenario in which the Goldstino superfield in an O'Raifeartaigh model is responsible for both supersymmetry breaking and R-symmetry breaking. In such models, the competing problems of generating sufficiently massive gauginos while preserving an acceptably light gravitino can be quite challenging. We show that by sharing the burdens of breaking supersymmetry and R-symmetry with a second field, these problems are easily solved even within the O'Raifeartaigh framework. We present explicit models realizing minimal gauge mediation with a gravitino mass in the eV range that are both calculable and falsifiable.Comment: 31 pages, 4 figures, references added, minor change

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders