Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

The implementation of computerised condition monitoring systems for the detection cutting tools’ correct installation and fault diagnosis is of a high importance in modern manufacturing industries. The primary function of a condition monitoring system is to check the existence of the tool before starting any machining process and ensure its health during operation. The aim of this study is to assess the detection of the existence of the tool in the spindle and its health (i.e. normal or broken) using infrared and vision systems as a non-contact methodology. The application of Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) combined with neural networks are investigated using both types of data in order to establish an effective and reliable novel software program for tool tracking and health recognition. Infrared and visual cameras are used to locate and track the cutting tool during the machining process using a suitable analysis and image processing algorithms. The capabilities of PCA and Discrete Wavelet Transform (DWT) combined with neural networks are investigated in recognising the tool’s condition by comparing the characteristics of the tool to those of known conditions in the training set. The experimental results have shown high performance when using the infrared data in comparison to visual images for the selected image and signal processing algorithms

Stability Constraints on Classical de Sitter Vacua

We present further no-go theorems for classical de Sitter vacua in Type II string theory, i.e., de Sitter constructions that do not invoke non-perturbative effects or explicit supersymmetry breaking localized sources. By analyzing the stability of the 4D potential arising from compactification on manfiolds with curvature, fluxes, and orientifold planes, we found that additional ingredients, beyond the minimal ones presented so far, are necessary to avoid the presence of unstable modes. We enumerate the minimal setups for (meta)stable de Sitter vacua to arise in this context.Comment: 18 pages; v2: argument improved, references adde

Cellular Active N-Hydroxyurea FEN1 Inhibitors Block Substrate Entry to the Active Site

The structure-specific nuclease human flap endonuclease-1 (hFEN1) plays a key role in DNA replication and repair and may be of interest as an oncology target. We present the first crystal structure of inhibitor-bound hFEN1 and show a cyclic N-hydroxyurea bound in the active site coordinated to two magnesium ions. Three such compounds had similar IC50 values but differed subtly in mode of action. One had comparable affinity for protein and protein– substrate complex and prevented reaction by binding to active site catalytic metal ions, blocking the unpairing of substrate DNA necessary for reaction. Other compounds were more competitive with substrate. Cellular thermal shift data showed engagement of both inhibitor types with hFEN1 in cells with activation of the DNA damage response evident upon treatment. However, cellular EC50s were significantly higher than in vitro inhibition constants and the implications of this for exploitation of hFEN1 as a drug target are discussed

Cellular metabolism constrains innate immune responses in early human ontogeny

Pathogen immune responses are profoundly attenuated in fetuses and premature infants, yet the mechanisms underlying this developmental immaturity remain unclear. Here we show transcriptomic, metabolic and polysome profiling and find that monocytes isolated from infants born early in gestation display perturbations in PPAR-γ-regulated metabolic pathways, limited glycolytic capacity and reduced ribosomal activity. These metabolic changes are linked to a lack of translation of most cytokines and of MALT1 signalosome genes essential to respond to the neonatal pathogen Candida. In contrast, they have little impact on house-keeping phagocytosis functions. Transcriptome analyses further indicate a role for mTOR and its putative negative regulator DNA Damage Inducible Transcript 4-Like in regulating these metabolic constraints. Our results provide a molecular basis for the broad susceptibility to multiple pathogens in these infants, and suggest that the fetal immune system is metabolically programmed to avoid energetically costly, dispensable and potentially harmful immune responses during ontogeny

Design and Implementation of IoT-based Low-Cost Smart Saline Micro Pump

The present healthcare scenario teaches quite a lot to humanity. The increasing ratio between patients and nursing staff deteriorates health care services. Simple saline can cause deadly patient situations and chaotic conditions for healthcare workers. A proper intravenous medication system can avoid reverse blood flow, blood clots, vein inflammation, extravasation, air embolism, and hypervolemia. This proposed research article is based on an Internet of Things-based low-cost smart saline micro pump for the healthcare system. The prime objective of this research article is to design an IoT-based micropump, and the micropump is placed between the saline bottle and the patient to control the flow precisely. The entire process is controlled by a mobile application to minimize the staff workload, time, and chaotic conditions. The controlled device has information like the working of the micropump, status parameters such as saline flow rate, saline injection time duration, the inflow of IV infusion to the patient, saline completion status, patient bed number, etc. Implementing the proposed system can be a stepping stone for new healthcare devices

A review on the latest advances in extraction and analysis of artemisinin

Introduction: Artemisinin (1), a well-known natural antimalarial drug, is a sesquiterpene lactone that contains a unique peroxide bridge. Since its discovery, the amount of research into the analysis of artemisinin has increased considerably, and it has been further intensified since the Noble Prize win by Tu Youyou in the year 2015 for the discovery of artemisinin. Objective: To review published literature on the extraction and analysis of artemisinin, published during 2017-present, and to present an appraisal of those methods. Methodology: Extensive literature search was carried out which involved, but not limited to, the use of, various databases, like Web of Knowledge, PubMed and Google Scholar, and relevant published materials including published books. The keywords used, in various combinations, with artemisinin being present in all combinations, in the search were artemisinin, Artemisia annua, analysis, extraction, quantitative, qualitative and quality control. Results: During the period covered in this review, there are several methods of analysis of artemisinin have been reported, the most of which were LC-based methods. However, the use of new methods like near infrared analysis, fluorometirc analysis and molecular imprinting, and a significant increase in the use of computational tools have been observed. Mainly several methods involving supercritical fluid extraction and ultrasound-assisted extraction of artemisinin have dominated the extraction area. Conclusions: Newer analytical tools, as well as improved protocols for the known analytical tools, for qualitative and quantitative determination of artemisinin (1), have been made available by various researchers during the period covered by this review. Supercritical fluid extraction and ultrasound-assisted extraction are still the methods of choice for extraction of artemisinin

Large Deviations for Stochastic Nematic Liquid Crystals driven by Multiplicative Gaussian Noise

We study a stochastic two-dimensional nematic liquid crystal model with multiplicative Gaussian noise. We prove the Wentzell-Freidlin type large deviations principle for the small noise asymptotic of solutions using weak convergence metho